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Shadow detection is a common computer vision task that identifies the location of shadows. It has been used as a key primitive for many high-level tasks such as object segmentation and video tracking. Due to the complexity and variety of shadows, it is challenging to design a one-size-fits-all shadow detection algorithm in real-world scenarios. Instead, it is often necessary in practice to pick the best shadow detection algorithm for a particular vision application. While shadow detection algorithms can be assessed by comparing the detected shadow with the ground truth, such ground truth is often unavailable in real-world vision systems consistently generating new data. In this paper, we propose a no-reference shadow detection quality assessment network (NSDQA-Net) to rank shadow detection algorithms without needing the ground truth. For a given image, the proposed assessment network first learns a reference map that compensates the false positives and false negatives of multiple input shadow detection algorithms. The reference map, as well as the original image and the input shadow detection results, are then used to regress the quality scores of the shadow detection methods. Our framework supports the assessment of one, two, or multiple algorithms in a single run, making it easier for deployment in practical scenarios. Experiments results show that the proposed network achieves optimal accuracy in no-reference shadow detection assessment. Relying on it for adaptive algorithm selection also improves the performance of shadow detection using a fixed algorithm on benchmark datasets. [Display omitted] • We identify a task of no-reference quality assessment in shadow detection. • We design a novel no-reference shadow detection quality assessment network (NSDQA-Net). • We experimentally demonstrate the state-of-the-art performance of the proposed network. [ABSTRACT FROM AUTHOR]

Facial information plays an important role in human communication, e.g., rich and nuanced facial expressions effectively convey emotions. Traditional data such as 2D facial images and videos are susceptible to perturbation from lighting and occlusion, while 3D static data such as mesh models lack the temporal information which is necessary to describe facial dynamics. Therefore, researches on 4D facial data (3D facial models together with time as the fourth dimension) have received considerable attention in recent years. 4D data can simultaneously reflect the complex facial temporal and space information. To fully explore these characteristics, we present a systematic overview of the 4D facial research in this paper. We give a review in terms of historical development of 4D facial datasets, acquisition process of these datasets, related algorithms and applications, and discussion of outstanding issues. We also analyze the 4D facial research works by summarizing and comparing them; in particular, we present the results on three kinds of tasks conducted on the 4D facial datasets, i.e., expression-related tasks (AU detection, expression recognition and retrieval), generation tasks (3D facial reconstruction, facial expression and facial animation generation), and other tasks (facial registration, facial recognition and facial disease diagnosis). Finally, we summarize the future research directions. [Display omitted] • We provide a comprehensive overview of a 4D facial dataset. • We classified and elaborated on the different facial studies conducted using 4D facial datasets. • We summarize the future research direction. [ABSTRACT FROM AUTHOR]

This paper introduces a two-stage approach that automatically generates 3D CAD models from 2D orthographic drawings. First, a pattern-matching algorithm is proposed to reconstruct a network of 3D edges by matching 2D edge features extracted from the multiple views of the 2D drawing. Second, starting from the resulting 3D wireframe and generated graph, a loop detection algorithm allows identifying possible loops of faces. Then, a clustering algorithm recognizes the faces from the set of detected loops. The reconstruction ends while trimming and stitching the faces to get a watertight ready-to-use 3D CAD model. This approach has been validated on a public dataset composed of several thousands of 3D shapes, and it achieved 99.59% of well-reconstructed models in F-score. • A rule-based approach to automatically reconstruct 3D CAD models from 2D drawings. • A pattern-matching algorithm to generate 3D wireframes from 2D drawings. • A loop detection algorithm using co-planarity criterion to reduce the search space. • A clustering algorithm to identify the faces from a set of 3D loops in a wireframe. [ABSTRACT FROM AUTHOR]

• The current 3D human body reconstruction technology requires a large number of 3D scanning equipment and a complex dynamic capture process, which significantly limits its rapid adoption in these application domains. The purpose of this article is to simplify the process of 3D reconstruction. • By combining deep learning methods, an end-to-end 3D human body reconstruction framework is proposed to achieve the goal of reconstructing a high-precision 3D human body model based on RGB images. [Display omitted] In recent years, with the improvement of artificial intelligence technology, it has become possible to reconstruct high-precision 3D human body models based on ordinary RGB images. The current 3D human body reconstruction technology requires complex external equipment to scan all angles of the human body, which is complicated to be implemented and cannot be popularized. In order to solve this problem, this paper applies deep learning models on reconstructing 3D human body based on monocular images. First of all, this paper uses Stacked Hourglass network to perform convolution operations on monocular images collected from different views. Then Multi-Layer Perceptrons (MLPs) are used to decode the encoded high-level images. The feature codes in the two views(main and side) are fused, and the interior and exterior points are classified by the fusion features, so as to obtain the corresponding 3D occupancy field. At last, the Marching Cube algorithm is used for 3D reconstruction with a specific threshold and then we use Laplace smoothing algorithm to remove artifacts. This paper proposes a dense sampling strategy based on the important joint points of the human body, which has a certain optimization effect on the realization of high-precision 3D reconstruction. The performance of the proposed scheme has been validated on the open source datasets, MGN dataset and the THuman dataset, provided by Tsinghua University. The proposed scheme can reconstruct features such as clothing folds, color textures, and facial details,and has great potential to be applied in different applications. [ABSTRACT FROM AUTHOR]

In this paper, we present a new volumetric ambient occlusion algorithm called Contextual Ambient Occlusion (CAO) that supports real-time clipping. The algorithm produces ambient occlusion images of exactly the same quality as Local Ambient Occlusion (LAO) while enabling real-time modification to the shape used to clip the volume. The main idea of the algorithm is that clipping only affects the ambient value of a small number of voxels, so by identifying these voxels and recalculating the ambient factor only for them, it is possible to significantly increase the rendering performance (by 2-5x) without decreasing the quality of the rendered image. Due to its fast performance, the algorithm is suitable for interactive environments where clipping changes could occur every frame. Additionally, the algorithm does not have any stereoscopic inconsistency, which makes it suitable for mixed reality environments. This paper is an extended version of the "Contextual Ambient Occlusion" article presented during the 2023 Graphics Interface conference, and includes, among other additions, the source code of the algorithm. [Display omitted] • Clipping only affects the ambient value of a small number of voxels. • It is more efficient to perform recalculation only on voxels affected by clipping. • Contextual Ambient Occlusion achieves same quality as Local Ambient Occlusion. • Contextual Ambient Occlusion is suitable for interactive environments. [ABSTRACT FROM AUTHOR]

Sankey diagrams are widely used to visualize event sequence data. However, when the data volume is large, its readability is affected by dense edge crossings, excessive swing amplitude, and small crossover angles, while it is computationally intensive to obtain an optimal layout. In this paper, we propose NeatSankey, a balanced method that generates Sankey diagrams smoothly. It can be laid out quickly with good readability when Sankey diagrams are very complex. At the same time, to comprehensively evaluate the readability of Sankey diagrams, we use three evaluation metrics: crossing number, swing amplitude, and layout coverage. Firstly, we use a heuristic layout algorithm and a force-directed algorithm to adjust the node layout to minimize the edge crossings and swing amplitude with edge widths considered. Secondly, to better reduce the dense confusion caused by edge crossings, we introduce a edge bundling algorithm based on attribute similarity. We present three evaluations: a comprehensive comparison of our results with state-of-the-art techniques, user studies with thirty volunteers, and a case study of two datasets. Our evaluations demonstrate the effectiveness and practicability of the NeatSankey. [Display omitted] • We propose a novel two-step algorithm to enhance the readability of Sankey diagrams. • NeatSankey can generate Sankey diagrams smoothly within a limited time. • We can bundle edges with different widths and show the exact connections. • We design evaluations which can measure the readability of Sankey diagrams perfectly. • We conduct three studies to show the effectiveness and practicability of NeatSankey. [ABSTRACT FROM AUTHOR]

• This work proposes a novel computational framework for design of planar gears. • This is achieved by iterative conjugation which is shown to converge within two steps. • A robust computational framework for planar sweeps is proposed for conjugation. Gears play a pivotal role in machine design. This paper proposes an algorithm to simplify the shapes of planar gears. This is achieved via iterative conjugation, using precise algebraic sweeps. The notion of shape simplification is introduced in a mathematically rigorous manner and it is shown that the conjugation process converges, yielding a pair of meshing gears that follow the desired motion. Simplified gear shapes may lead to improved mechanical characteristics and reduction in manufacturing costs. The generality of algebraic sweeps allows precise design of gears with freeform shapes and non-uniform motion transmission. Moreover, the computational framework proposed in this paper is versatile, with applications beyond gear design. A variety of examples from an implementation of our algorithm, that offers topological guarantees, are presented, which demonstrate the robustness and efficacy of our approach. [ABSTRACT FROM AUTHOR]

Recent research in arbitrary style transfer has highlighted challenges in maintaining the balance between content structure and style patterns. Moreover, the improper application of style patterns onto the content image often results in suboptimal quality. In this paper, a novel style transfer network, called MCNet, is proposed. It is based on multi-feature correlations. To better explore the intrinsic relationship between the style image and the content image and to transfer the most suitable style onto the content image, a novel Global Style-Attentional Transfer Module, named GSATM, is introduced in this work. GSATM comprises two parts: Forward Adaptive Style Transformation (FAST) and Delayed Style Transformation (DST). The former analyzes the relationship between style and content features and fine-tunes the style features, whereas the latter transfers the content features based on the fine-tuned style features. Moreover, a new encoding and decoding structure is designed to effectively handle the output of GSATM. Extensive quantitative and qualitative experiments fully demonstrate the superiority of our algorithm. Project page: https://github.com/XiangJinCherry/MCNet. [Display omitted] • We propose a new algorithm that can perform arbitrary style transfer. • We propose a novel Global Style-Attentional Transfer Module (GSATM). • We design an Adaptive Unified Decoder to fuse the outputs of the multiple GSATMs. [ABSTRACT FROM AUTHOR]

The automatic shape description of solids is a problem of interest in manufacturing engineering, amongst other related areas. This description can be either geometrical or topological in nature and can be applied to either surfaces or solids (embedded manifolds). Topological descriptions are specially interesting for the problem of shape comparison and retrieval, where one wants to know if a given shape resembles some other known shape. Some popular topological descriptions use Morse theory to study the topology of manifolds and encode their shape characteristics. A Morse function f is defined on the manifold and the manifold's shape is indirectly studied by studying the behavior of the critical points of f. This family of methods is well defined for surfaces but does not consider the case of solids. In this paper we address the topological description of solids using Morse theory. Our methodology considers three cases: solids without internal boundaries, solids with internal boundaries and thin-walled solids. We present an algorithm to identify topological changes on these solids using the principle of shape decomposition by Morse handles. The presented algorithm deals with Morse functions that produce parallel planar level sets. Future endeavors should consider other candidate functions. [Display omitted] • We show how the Reeb graph cannot describe the shape of general solids • We present a methodology to address the shape description of general solids • We automatically identify the critical points of a solid given its B-Rep. • We apply our methodology to several datasets for Additive Manufacturing [ABSTRACT FROM AUTHOR]

The primary purpose of this paper is to realize robust place recognition algorithms towards simultaneous viewpoint and condition changes, and provide satisfactory computational efficiency. In this paper, we significantly improve the viewpoint invariance of the SeqSLAM algorithm by using state-of-the-art deep learning techniques to generate robust feature representations of images and develop the SeqCNNSLAM . Experimental results show that SeqCNNSLAM outperforms state-of-the-art place recognition systems in most cases, such as, when precision is maintained at 100%, the maximum recall obtained by SeqCNNSLAM is 50% higher than SeqSLAM on the Norland dataset with simultaneous condition change and 12.5% viewpoint change. Besides, we develop an acceleration method called A-SeqCNNSLAM , which exploits the location relationship between the matching images of adjacent images to reduce the matching range of the current image. Experimental results demonstrate that an acceleration of  ∼  5 times is achieved with minimal accuracy degradation of  ∼  5%. Finally, to enable A-SeqCNNSLAM adaptability in new environments, O-SeqCNNSLAM is devised for the online parameter adjustment in A-SeqCNNSLAM. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for finding all 2D intersection regions between disk B-spline curves (DBSCs), which is very crucial for DBSC’s wide applications such as computer calligraphy, computer 2D animations, and non-photorealistic rendering. As a DBSC represents a region on a plane, the intersection of two DBSCs is a 2D region. To determine the region, the key is to compute the intersection points of the boundaries of two DBSCs. In our algorithm, the boundary of a DBSC is decomposed into four components: the upper boundary, the lower boundary, the start arc, and the end arc. The intersection of two DBSCs can be converted into the intersections between these four components. The main difficulty is to find the intersection involving the upper and lower boundaries of the two DBSCs, as they are variable offsets from the skeletons of the DBSC that are B-spline curves. In our approach, first the DBSCs are subdivided into several disk Bézier curves (DBCs). Therefore the problem of computing intersections of the DBSCs is converted into computing intersection of two DBCs. Then, the disk Bézier clipping method is proposed to exclude regions that have no intersection for the intersection of the two DBCs. In the case of where there is an intersection, we calculate the comparatively rough intersection to be used as initial values for later refinement through the disk Bézier clipping method. Besides, high precision (up to 10e − 15) intersections are achieved by using the Newton’s iteration, which is quadratic convergent. The experimental results demonstrate that our algorithm can very efficiently compute all intersections between DBSCs with high precision. Our main contributions in this paper are as follows. First, for the first time, we give the direct parametric expression of DBSC’s boundary, which can be simply and conveniently used to compute the properties of DBSC’s boundary. Second, our proposed approach of calculating high-accuracy intersections of DBSCs makes DBSC a flexible and effective stroke representation that can be applied to further research such as corresponding computation, automatically coloring, region detection and so on. [ABSTRACT FROM AUTHOR]

• An efficient radial-basis-function guided segmentation method is proposed to generate smooth and contiguous model partition based on surface attributes, which serves as the initial segmentation result. • A differential evolution based smoothing algorithm is introduced to optimize the cut interfaces of segmented parts constrained by the prescribed minimal printing thickness. • A refinement method for part extractability is designed to detect the infeasible segmented parts and compute division planes to further sub-divide them to ensure the extractability of all split parts. • The proposed technique is applied on a variety of models, and the experimental results shows its advantages over prior methods. Additionally, printed physical objects are provided as a proof of its reliability on current mainstream printers. [Display omitted] Volume segmentation based on surface attributes is an essential problem in multi-material fabrication and model packing. In practice, current mainstream fabrication techniques have difficulties in yielding models with diverse surface attributes in one pass owing to their craft limitations, making model segmentation a sensible choice for model realization. Partitioning 3D objects into single-attribute volumetric parts prevents fabricating models with different material in a single printing procedure, whereas the arisen challenge is to determine a reliable segmentation solution that is able to handle complicated models in various use scenarios. To achieve this goal, we propose a novel volume partition algorithm generating feasible volumetric parts, each of which is affiliated with one single surface attribute. Our technique enables model segmentation with least conflict and constrained wall thickness so that each volumetric segment can be realized independently by 3D-printing. Generally, it starts with computing a partition proposal guided by radial-based-function iso-surface, then optimizes segmentation interface with a prescribed minimal printing thickness to produce high-quality surface for every volumetric part, and finally splits unextractable volumetric parts into smaller sub-volumes to ensure assemblability of the whole model. As previous methods do not work well in optimizing segment interface for printing, we propose a differential evolution based smoothing algorithm to generate smooth and continuous interface, declining the risk of collision between adjacent volumetric parts. Extensive experimental results are provided in this paper to demonstrate the effectiveness and quality of our proposed technique, showing its advantages on model manufacture over prior methods. [ABSTRACT FROM AUTHOR]

• A simple and effective ridge valley point recognition method is present, which greatly reduces the number of potential feature points and improves the robustness of the recognition. • A freeform feature enhancement algorithm based on position and normal constraints is proposed. By different settings, several enhancement effects can be realized, such as preserving the original shape as much as possible, sharpen it or recovering a totally sharp edge. • A point cloud parameterization method based on feature line guidance is introduced to reduce the number of unknowns by 2/3 and eliminate the lateral sliding of points. [Display omitted] Ridge-valley features are important elements of a model. To recognize these features from point cloud, this paper introduces a new criterion named Extremal Point Distance (EPD) to greatly reduce the number of potential feature points and locate feature position more accurately. On this basis, a feature enhancement algorithm is proposed. The algorithm adjusts the coordinates of feature regions by minimizing a linear objective function consisting of expected position and normal, which can ensure the accurate sampling of feature position. We also present a parameterization method to eliminate the lateral sliding of feature points and reduce the number of unknowns in the objective function. Since the EPD criterion only depends on the changing trend, rather than the absolute value of the curvature, our algorithm can infer the expected position and normal with a large neighborhood radius, which makes it robust to noise. Experiments show that our algorithm can adjust the feature amplitude and sharpness freely, and achieve satisfactory results in feature recognition, feature enhancement and sharp feature restoration. [ABSTRACT FROM AUTHOR]

• Propose a fast recolouring algorithm for dichromacy compensation. • The algorithm can compensate contrast loss while preserving the naturalness. • Automatically adapt the balance between contrast enhancement and naturalness preservation to individual images. • Provide two fast solvers for achieving the optimized recolouring results in nearly real time. [Display omitted] People with colour vision deficiency (CVD) may have difficulty recognising or discriminating colours. To enhance their visual details, some methods have been developed to enhance colour contrast. Recently, researchers realized the importance of preserving naturalness in the processed images to avoid decreasing the quality of vision (QOV) and state-of-the-art image recolouring methods succeeded in realising both contrast enhancement and naturalness preservation by utilising optimisation model. However, the high computational cost of these methods prevents their wide application in daily lives. Moreover, these methods cannot automatically resolve the trade-off between contrast enhancement and naturalness preservation. This paper proposes Optimized Dichromacy Projection (ODP) as a novel high-speed image recolouring technique for dichromacy compensation. ODP achieves both contrast enhancement and naturalness preservation by computing an optimized projection from the colour gamut of normal vision to the colour gamut of dichromacy and can automatically adapt the weight of contrast enhancement and naturalness preservation to the property of individual images. Qualitative, quantitative, and subjective evaluation experiments show that the proposed method can generate images of qualities competitive to the state-of-the-art methods while drastically improving computation time. [ABSTRACT FROM AUTHOR]

• Reviews the existing surface remeshing techniques evolved during the last decade that attempt to solve surface remeshing as an optimization problem and achieve the balance between the typical goals of surface remeshing. • Analyzes the performance parameters of existing surface remeshing techniques. • Identifies the drawbacks in the existing techniques. • Suggests a few improvements in the techniques to enhance the results. Direct triangular surface remeshing algorithms work directly on the surface meshes without involving any complex parameterization techniques. The typical goal of surface remeshing is to find a mesh that is a faithful approximation of the input mesh that maintains the geometric fidelity between input and output meshes, achieve a lower bound on the minimal angles to enhance high element quality while maintaining vertex regularity and sharp feature preservation of the input mesh. The goal of each surface remeshing algorithm varies as per the requirement of the end application and thus achieving a balance between all common goals is a challenging task in remeshing. In this paper, a survey of numerous direct surface remeshing algorithms that have been developed over the past decade is presented. A framework of direct surface remeshing is defined and various phases of the framework are discussed in detail to give new insights into both existing methods and issues. A detailed analysis of how significant challenges have already been overcome and promising perspectives of various methods are presented. [ABSTRACT FROM AUTHOR]

• Introduction of Riemannian global illumination. • A path tracer algorithm to approximate the solution of the Riemannian global illumination. • A map of the algorithm to the GPU, using the RTX platform. • We apply the Non-Euclidean path tracer to render "Photorealistic" inside views of the 3D flat torus, Poincaré sphere, and the hyperbolic mirrored dodecahedron. These are examples of the Euclidean, spherical, and hyperbolic spaces: the Thurston classical geometries. This paper presents a novel path tracer algorithm for immersive visualization of Riemannian manifolds. To do this, we introduce Riemannian illumination, a generalization of classical Computer Graphics illumination models. In this context, global light transport is expressed by extending the rendering equation to Riemannian manifolds. Using Monte Carlo integration to solve this equation results in the novel path tracer for Non-Euclidean spaces. We discuss its basic principles, as well as the general CPU algorithm. Additionally, we discuss in detail how to implement a GPU version, using the RTX pipeline. Finally, we apply the algorithm to render "photorealistic" inside views of the flat torus, Poincaré sphere, and the hyperbolic mirrored dodecahedron. These are examples of Euclidean, spherical, and hyperbolic spaces: the Thurston classical geometries. [ABSTRACT FROM AUTHOR]

A stencil is a thin sheet of material, such as paper, plastic, or metal, with certain patterns cut from it. Applying a pigment through the cut-out holes produces a design on an underlying surface. Using multiple overlapping stencil layers, artists can create intricate, yet reproducible imagery on a variety of surfaces. Traditionally, artists have to design not only the final appearance, but also each individual stencil layer. A stencil layer needs to be connected, geometrically simple, and physically stable. Taking all these constraints into account during the design process is difficult and unintuitive even for skilled artists. In this paper, we propose a system which separates the artistic design stage from the complex and tedious task of stencil creation. For a given user design, our algorithm automatically generates a set of stencil layers satisfying all required properties. The task is formulated as a constrained energy optimization problem and solved efficiently. Experiments, including a user study, are carried out to examine the complete algorithm as well as each individual step. [ABSTRACT FROM AUTHOR]

• We introduce a weighted total variation diffusion model. • We apply the model for mesh and point cloud decomposition. • We propose to solve the shape decomposition optimization problem by augmented Lagrangian method. • Experiments show that the shape decomposition method can produce results with piecewise constant parts and clear boundaries. One challenge in shape decomposition is to capture correct boundaries between different parts and get piecewise constant results. Based on the good edge-preserving and sparsity properties of total variation regularization, this paper introduces a novel diffusion model by minimizing weighted total-variation energy with Dirichlet boundary constraints. By the total variation diffusion model, we propose an edge-preserving shape decomposition optimization model, which can be solved effectively by augmented Lagrangian method with each subproblem having closed form solution. A number of experiments display that our method can produce segmentation results with piecewise constant parts and feature-preserving boundaries for both meshes and 3D point clouds, especially for shapes with sharp features. In addition, for mesh segmentation, our results compare favorably to those obtained by several existing techniques when evaluated on the Princeton Segmentation Benchmark. Furthermore, the quantitative errors show that the algorithm is robust numerically and the computational costs are reasonable. [ABSTRACT FROM AUTHOR]

• Discretization of Morse theory has led to different notions of critical sets. • The various notions of PL critical points given in the literature are equivalent. • A correspondence exists between PL critical points and discrete Morse cells. • The correspondence requires an optimality condition called relative perfectness. • An algorithm builds relative perfect gradient vector fields up to dimension 3. Piecewise-linear (PL) Morse theory and discrete Morse theory are used in shape analysis tasks to investigate the topological features of discretized spaces. In spite of their common origin in smooth Morse theory, various notions of critical points have been given in the literature for the discrete setting, making a clear understanding of the relationships occurring between them not obvious. This paper aims at providing equivalence results about critical points of the two discretized Morse theories. First of all, we prove the equivalence of the existing notions of PL critical points. Next, under an optimality condition called relative perfectness, we show a dimension agnostic correspondence between the set of PL critical points and that of discrete critical simplices of the combinatorial approach. Finally, we show how a relatively perfect discrete gradient vector field can be algorithmically built up to dimension 3. This way, we guarantee a formal and operative connection between critical sets in the PL and discrete theories. [ABSTRACT FROM AUTHOR]

• We propose a novel algorithmic pipeline for modeling piecewise planar shapes based on clustering. Our algorithm is computationally efficient and resistant to noise. • We give a set of strategies on extracting the polygonal representation of a facet and building the face adjacency graph, which leads to the final compact planarization representation. • We also introduce a regularization technique to encourage the orthogonality between facing directions, which is further transformed into a purely convex optimization problem. Piecewise planar 3D objects are very common in digital furniture manufacturing. In this paper, we propose a novel method for automatic reconstruction of 3D objects with planar facets from unorganized point clouds. We formulate this problem into a point clustering problem where the key difficulty lies in consolidating co-planar points into a cluster. In order to achieve this purpose, the first step is to triangulate the input point cloud into a mesh (may have over connectivity) that is a super-set of the underlying manifold mesh surface. Then the hundreds of thousands of normal vectors of triangles, after being mapped onto a Gauss sphere, are capable of reporting reliable facing directions of the faces of the final 3D model. After grouping the points based on co-planarity, we fit each cluster with a planar facet and then assemble them into a piecewise planarization representation of the whole model. We further introduce an additional regularization term to meet the orthogonality requirement on a particular occasion, and then transform this problem into a purely convex optimization problem. Our method is efficient and requires just a few parameters. Extensive experimental results show that it is able to handle point clouds with various levels of noise and yield a desirable piecewise planar 3D model with a clean and compact representation. [ABSTRACT FROM AUTHOR]

• Textile structures can be considered as knotted structures embedded in a thickened torus. • To facilitate computation with these structures, we develop an encoding similar to the Gauss code. • This encoding can give rise to non-realizable textiles – we describe an algorithm for determining realizability directly from the code itself. • We employ this algorithm to facilitate an enumeration all isotopically distinct oriented textile structures with up to three crossings. A textile structure is a periodic arrangement of threads in the thickened plane. A topological classification of textile structures is harder than for classical knots and links that are non-periodic and restricted to a bounded region. The first important problem is to encode all textile structures in a simple combinatorial way. This paper extends the notion of the Gauss code in classical knot theory, providing a tool for topological computation on these structures. As a first application, we present a linear time algorithm for determining whether a code represents a textile in the physical sense. This algorithm, along with invariants of textile structures, allowed us for the first time to classify all oriented textile structures woven from a single component up to complexity five. [ABSTRACT FROM AUTHOR]

• An agent in a crowd simulation typically uses multiple navigation algorithms. • We convert the output of each navigation algorithm to a topological strategy. • We let an agent systematically detect and resolve conflicts between its strategies. • Thus, we synchronize an agent's algorithms and bridge conceptual gaps between them. • Conflict resolution helps improve the behavior of agents and of the overall crowd. We present a novel topology-driven method for enhancing the navigation behavior of agents in virtual environments and crowds. In agent-based crowd simulations, each agent combines multiple navigation algorithms for path planning, collision avoidance, and more. This may lead to undesired motion whenever the algorithms disagree on how an agent should pass an obstacle or another agent. In this paper, we argue that all navigation algorithms yield a strategy : a set of decisions to pass obstacles and agents along the left or right. We show how to extract such a strategy from a (global) path and from a (local) velocity. Next, we propose a general way for an agent to resolve conflicts between the strategies of its algorithms. For example, an agent may re-plan its global path when collision avoidance suggests a detour. As such, we bridge conceptual gaps between algorithms, and we synchronize their results in a fundamentally new way. Experiments with an example implementation show that our strategy concept can improve the behavior of agents while preserving real-time performance. It can be applied to many agent-based simulations, regardless of their specific navigation algorithms. The concept is also suitable for explicitly sending agents in particular directions, e.g. to simulate signage. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new method to control scene sampling in complex ray-based rendering environments. It proposes to constrain image sampling density with a combination of object features, which are known to be well perceived by the human visual system, and image space saliency, which captures effects that are not based on the object''s geometry. The presented method uses Non-Photorealistic Rendering techniques for the object space feature evaluation and combines the image space saliency calculations with image warping to infer quality hints from previously generated frames. In order to map different feature types to sampling densities, we also present an evaluation of the object space and image space features'' impact on the resulting image quality. In addition, we present an efficient, adaptively aligned fractal pattern that is used to reconstruct the image from sparse sampling data. Furthermore, this paper presents an algorithm which uses our method in order to guarantee a desired minimal frame rate. Our scheduling algorithm maximizes the utilization of each given time slice by rendering features in the order of visual importance values until a time constraint is reached. We demonstrate how our method can be used to boost or stabilize the rendering time in complex ray-based image generation consisting of geometric as well as volumetric data. [Copyright &y& Elsevier]

• We have proposed a novel method for detecting and locating local extrema over mesh edges, which effectively reduces fragmentation and fluctuation of feature lines. • We have leveraged integral invariants for the extraction of view-independent feature lines, which are capable of capturing features of small scales when compared to that of mesh elements. • We have demonstrated the effectiveness of our proposed method in generating coherent and smooth feature lines while preserving fine details. Feature lines such as ridge-valley lines can be defined as the loci of points which maximize a certain geometric property (e.g. the principal curvature) along the corresponding "critical directions" (e.g. the principal direction of curvature). Such extrema over mesh edges are often determined by zero-crossings of directional derivatives. As a result, lines generated by existing algorithms suffer frequently from fragmentation (gaps on lines) and fluctuation (lack of smoothness). As such, we propose a novel method for tracing such lines. Points on feature lines, i.e. extrema over mesh edges, are detected and located by interpolating extrema in the vicinity of mesh vertices, which effectively reduces fragmentation and fluctuation of lines. Meanwhile, the majority of the existing algorithms for feature lines extraction employ high-order derivatives of the underlying surfaces for estimating both the geometric property and the critical direction. Estimation of differential invariants including curvature typically requires at least 2-ring neighborhoods of mesh vertices, making such quantities intrinsically incapable of capturing "local" features. By leveraging integral invariants, which can be defined over an appropriately small neighborhood, we are able to extract features of small scales when compared to that of mesh elements. In this paper, we demonstrate the effectiveness of our proposed method in generating coherent and smooth feature lines while providing more desirable details. [ABSTRACT FROM AUTHOR]

Highlights • The proposed framework is an effective and flexible tool for structure-texture decomposition smoothing. • Exhibits good response to the image which has low-contrast details. • The computational time is competitive to the others state-of-the-art algorithms. Graphical abstract A comparison of the proposed algorithm's results using different guided edge-preserving filters. Abstract Structure-texture decomposition smoothing has been extensively studied due to its wide range of applications in computational photography and image processing. In this paper, we propose a new structure-texture decomposition algorithm which is based on two fundamental ideas: (1) guidance image and (2) iterative smoothing. The guidance image is generated by mitigating high-frequency oscillatory components in the original image. The result is then incorporated in a new generic iterative framework which makes use of well-known guided edge-reserving filters such as bilateral filter (BF), guided filter (GF), domain transform filter (DTF), and the extended Bayesian model averaging filter (BMA) called guided Bayesian model averaging filter (GBMA) to achieve texture smoothing. We have presented a detailed study of the proposed algorithm including: guidance image generation, an evaluation of the guided edge-preserving filters which are incorporated in the proposed iterative framework, the number of iterations for the proposed iterative structure, and the selection of guided edge-preserving filter. We demonstrate that the proposed method is a flexible and effective tool for a wide range of image editing applications including: image abstraction, color pencil drawing, content-aware image resizing, and texture editing. In particular, the proposed approach has the best performance in structure-texture decomposition for an image with low-contrast features. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we propose a new region-growing based iso-surface extraction algorithm that can generate high-quality curvature-adaptive semi-regular meshes, preserve sharp features and will extract all the disjoint components of the iso-surface. More importantly, in this paper, we propose a novel normal consistency constraint that ensures the intersection of the Delaunay sphere of the new triangle and the iso-surface is a topological disk, an important property that makes the new algorithm very robust when dealing with large scale of volumetric datasets of complex topology and geometry. [Copyright &y& Elsevier]

Abstract: The watershed transform from markers is a very popular image segmentation operator. The image foresting transform (IFT) watershed is a common method to compute the watershed transform from markers using a priority queue, but which can consume too much memory when applied to three-dimensional medical datasets. This is a considerable limitation on the applicability of the IFT watershed, as the size of medical datasets keeps increasing at a faster pace than physical memory technologies develop. This paper presents the O-IFT watershed, a new type of IFT watershed based on the O-Buffer framework, and introduces an efficient data representation which considerably reduces the memory consumption of the algorithm. In addition, this paper introduces the O-Buckets, a new implementation of the priority queue which further reduces the memory consumption of the algorithm. The new O-IFT watershed with O-Buckets allows the application of the watershed transform from markers to large medical datasets. [Copyright &y& Elsevier]

Abstract: This paper explores a new family of 2D interpolating subdivision schemes that calculate subdivision points from tangent specifications. In this approach each level of subdivision drives the curve toward its specified tangents. The paper describes the underlying algorithmic formulation, and outlines a number of variations, which differ in how subdivision points are computed from tangents or in how tangents are derived. The different characteristics of these variations are shown to provide an interesting range of shapes, giving a high degree of artistic control. Each variation is shown to guarantee C1 continuity except for special identifiable cases, and some of these variations can produce circles. A number of examples are explored that demonstrate the power of the approach as a modeling tool for constructing complex curves, and a comparison is made with curves produced by the Kobbelt subdivision scheme. [Copyright &y& Elsevier]

Abstract: A new corner detector for planar curves is presented in this paper. This algorithm finds corner by sliding set of three rectangles along the curve and counting number of contour points lying in each rectangle. This structure incorporates more than one view of given shape which is a key to find all corners successfully. Proposed technique was found very consistent with human vision system. This is an efficient method, as it does not involve calculation of cosine angle and curvature. Criteria for evaluation of corner detection algorithms are proposed in this paper. A comparative study of six corner detectors (including proposed algorithm) is also presented. This technique is very useful to detect corners from noisy shapes and natural object boundaries. [Copyright &y& Elsevier]

This paper presents a novel gradient-based image completion algorithm for removing significant objects from natural images or photographs. Our method reconstructs the region of removal in two phases. Firstly, the gradient maps in the removed area are completed through a patch-based filling algorithm. After that, the image is reconstructed from the gradient maps by solving a Poisson equation. A new patch-matching criterion is developed in our approach to govern the completion of gradient maps. Both the gradient and the color information are incorporated in this new criterion, so a better image completion result is obtained. Several examples and comparisons are given at the end of the paper to demonstrate the performance of our gradient-based image completion approach. [Copyright &y& Elsevier]

Polyhedral mesh surfaces are widely utilized to represent objects reconstructed from 3D ranged images. In computer-aided engineering, it is desired not only to observe but also measure these three-dimensional (3D) objects. This paper presents an approach to measure the curve distance between two points on a polyhedral surface in the manner that simulates dragging a tapeline at the two points. After generating the initial measurement curve through the leading points in linear computing time, an iteration algorithm is presented to approximate stretching the measurement curve on the given polyhedral surface; as an option, the obtained measurement curve can be further stretched to leave the measured surface in some concave places—this looks like what a tapeline behaves in reality. This novel interactive tool allows users to perform measurement tasks in an intuitive and natural way in virtual space. Our implementation algorithm can be completed in real time on a standard PC. At the end of the paper, applications of this tool are given to demonstrate its functionality. [Copyright &y& Elsevier]

In this paper we introduce a novel approach for progressive transmission of three-dimensional (3D) triangular meshes. This algorithm is based on a new reversing approach of the irregular mesh subdivision that enables a wavelet representation of any mesh geometry. In this paper, we show how to achieve progressive compression of 3D models by transmitting more and more wavelet coefficients computed from the original mesh vertices coordinates. The connectivity of the reconstructed mesh remains the same as the original one, but its geometry is progressively refined by means of bitplane encoding. This approach processes directly floating point coordinates which is the most common representation for 3D meshes, and does not need quantization, which is a lossy transformation. Experimental results are given and demonstrate the efficiency of our encoding scheme versus other approaches. [Copyright &y& Elsevier]

This paper presents a progressive algorithm by which we can narrow down the searching domain for face identification and reconstruct various 3D objects from a single freehand line sketch drawing in short time. The sketch drawings served as an input for the reconstruction process in this paper are obtained from an inaccurate freehand sketch of a 3D wireframe object, which is the edge–vertex graph without any removal of hidden lines. The algorithm is executed through two stages. First, at the face identification stage, every possible faces are generated from the sketch and they are classified into implausible faces, basis faces and minimal faces by means of the geometrical and topological constraints in order to reduce the searching space. The proposed algorithm searches minimal space of the faces so that the actual faces of the given object could be identified in short time. Second, at the object reconstruction stage, we calculate a 3D structure progressively by optimizing the vertices coordinates of the object in accordance with the sketching order of faces. This progressive method reconstructs the most plausible 3D object in a short time by applying the 3D constraints that are derived from the relationship between an object and its sketch drawing in the optimization process. In addition, this method makes it possible for designers to change their viewpoints while sketching. In this paper, we are describing the progressive reconstruction algorithm, and giving the results of the implementation. [Copyright &y& Elsevier]

This paper proposes a mesh simplification algorithm using a discrete curvature norm. Most of the simplification algorithms are using a distance metric to date. The distance metric is very efficient to measure geometric error, but it is difficult to distinguish important shape features such as a high-curvature region even though it has a small distance metric. We suggest a discrete curvature norm to measure geometric error for such features. During simplification the new vertex resulted from an edge collapse takes a position using a butterfly subdivision mask to minimize geometric error. This paper shows that simplification results have smaller geometric errors than previous works, when a discrete curvature norm and a distance metric are together applied to its criterion. [Copyright &y& Elsevier]

While many image composition and synthesis techniques have been proposed, neither existing work nor professional image editing softwares such as Adobe Photoshop © provide a program explicitly for the task of realistically swapping regions within a single image . In this paper, we present an easy-to-use image-editing tool explicitly for that purpose, named as PatchSwapper. Users can simply determine the centre and radius of a pair of candidate regions or specify arbitrary borders by sketches; then, the swapping step is automatically and optimally executed. A graph-based approach is designed to find the optimal borders of two irregular regions to avoid generating visible seams. We use this approach to handle both non-transformed and transformed patches. For non-transformed cases, we not only achieve realtime performance with CPU multi-thread implementation, we also provide a location recommendation algorithm to help users find the appropriate exchangeable areas. For transformed patches, our method searches for the optimal transformation to generate interesting appearance changes on both the source and target locations. A Poisson color blending is performed onto the stitched patches. Overall the proposed approach is not only suitable for swapping image objects of any shapes but also for some other applications, e.g., image completion and composition. The experiments demonstrate that common images often contain potentially exchangeable areas and that large content variations can be obtained by simply swapping their locations. [ABSTRACT FROM AUTHOR]

User interfaces based on mid-air gesture recognition are expected to become popular in the near future due to the increasing diffusion of virtual, mixed reality applications and smart devices. The design of this kind of interfaces would be clearly helped by the availability of simple and effective methods to compare short 3D trajectories, allowing fast and accurate recognition of command gestures given a few examples. This approach, quite popular in 2D touch-based interfaces with the so-called “dollar” algorithm family, has not been deeply investigated for 3D mid-air gestures. In this paper, we explore several metrics that can be used for mid-air gesture comparison and present experimental tests performed to analyze their effectiveness on practical tasks. By adopting smart choices in gesture traces processing and comparing, it was possible to obtain very good results in the retrieval and recognition of simple command gestures, from complete or even partial hand trajectories. The approach was also extended in order to recognize gestures characterized by both hand and finger motions and tested on a recent benchmark, reaching state of the art performances. [ABSTRACT FROM AUTHOR]

We propose a novel fully convolutional network architecture for shapes, denoted by Shape Fully Convolutional Networks (SFCN) . 3D shapes are represented as graph structures in the SFCN architecture, based on novel graph convolution and pooling operations , which are similar to convolution and pooling operations used on images. Meanwhile, to build our SFCN architecture in the original image segmentation fully convolutional network (FCN) architecture, we also design and implement a generating operation with bridging function. This ensures that the convolution and pooling operation we have designed can be successfully applied in the original FCN architecture. In this paper, we also present a new shape segmentation approach based on SFCN. Furthermore, we allow more general and challenging input, such as mixed datasets of different categories of shapes which can prove the ability of our generalisation. In our approach, SFCNs are trained triangles-to-triangles by using three low-level geometric features as input. Finally, the feature voting-based multi-label graph cuts is adopted to optimise the segmentation results obtained by SFCN prediction. The experiment results show that our method can effectively learn and predict mixed shape datasets of either similar or different characteristics, and achieve excellent segmentation results. [ABSTRACT FROM AUTHOR]

3D surface offsetting is a fundamental geometric operation in CAD/CAE/CAM. In this paper, we propose a super-linear convergent algorithm to generate a well-triangulated and feature-aligned offset surface based on particle system. The key idea is to distribute a set of moveable sites as uniformly as possible while keeping these sites at a specified distance away from the base surface throughout the optimization process. In order to make the final triangulation align with geometric feature lines, we use the moveable sites to predict the potential feature regions, which in turn guide the distribution of moveable sites. Our algorithm supports multiple kinds of input surfaces, e.g., triangle meshes, implicit functions, parametric surfaces and even point clouds. Compared with existing algorithms on surface offsetting, our algorithm has significant advantages in terms of meshing quality, computational performance, topological correctness and feature alignment. [ABSTRACT FROM AUTHOR]

In this paper, to recover the missing geometry details on 3D surfaces, we develop a novel geometry detail recovery algorithm for 3D surfaces based on Empirical Mode Decomposition (EMD). EMD is a powerful tool for processing non-linear and non-stationary signals and has been successfully used in 3D surface analysis and processing. Given a signal defined on 3D surface, EMD could represent the signal in a multi-scale fashion and decompose the signal into a number of Intrinsic Mode Functions (IMFs) and a residue, which usually encode the multi-level finer-scale details and the overall shape of the signal, respectively. Benefiting from the multi-scale representation of geometry details, the EMD-based multi-scale geometry detail recovery algorithm is developed. Our strategy starts from an initial smooth filling of a hole and then transfers the desirable details from the most similar region to the smoothly-filled surface within the framework of EMD. Taking the advantages of EMD, we first apply EMD on the whole completed surface to obtain the multi-scale representation of geometry details. Then, the most similar region corresponding to the hole region is located by the patch descriptor constructed from Heat Kernel Signature (HKS). Finally, the missing geometry details can be effectively recovered by transferring the geometry details from the found similar region to the smoothly-filled surface. Traditional methods, such as context-based methods or example-based methods, usually cut the similar patch and paste them onto the hole region, and they require to match with the hole boundary, are complex in general. In contrast, our method is simple and can transfer different scale details individually or in a concerted way, which makes our algorithm more flexible and can achieve versatile detail recovery results. Comprehensive experiments and quantitative comparisons on popular models have been used to demonstrate the effectiveness of our EMD-based multi-scale geometry detail recovery algorithm. [ABSTRACT FROM AUTHOR]

Shape optimization often takes into account both inner and outer surfaces to achieve the design goals. The inner surface produced by existing methods is usually not support-free, which results in additional interior support structures during the printing process, thereby disrupting the design goals. In this paper, we present a simple and novel hollow-to-fill algorithm to guarantee the support-free property of inner surfaces for shape optimization. By analyzing the support-free conditions, three types of voxel-based support-free interior structures are proposed to compute inner surfaces. Given a voxelized model and the optimization goal, we first hollow out the model until it becomes a shell, whose thickness is determined by the physical material properties, and then add the support-free structures to optimize the inner surface, and finally refine the inner surface from bottom to top to minimize the optimization objective while maintaining the support-free property. Furthermore, shape deformation and extra weights are also utilized to optimize the shape for design goals. We demonstrate the feasibility and practicability of our method in three modes of balanced object design, where the physical mass properties of rigid objects are satisfied for the purpose of 3D printing. [ABSTRACT FROM AUTHOR]

Optic disc (OD) localization plays an important role in the automatic screening of ocular fundus diseases. However, it is still a challenge at present to balance the accuracy and efficiency of the OD localization for various of retinal fundus images. In this paper, we propose a new framework to integrate two classes methods based on image intensity and vascular information to obtain the OD location. The classification algorithm within the framework is based on a verification model. Firstly, an OD candidate region is obtained by image intensity. Secondly, the candidate region is validated by verification model. If the verification is passed, the corresponding position of the region is determined as the OD center. Otherwise, the OD is located by the parabola fitting of the main blood vessels and the relocation. The proposed method was evaluated on four public databases STARE, DRIVE, DIARETDB0 and DIARETDB1, and the accuracy rate was 96.3%, 100%, 100% and 100%, respectively. The running time is 0.05 s, 0.03 s, 0.13 s and 0.12 s per image through the validation in each database, while the time spent on images failed in verification is about 0.49 s, 0.38 s, 2.21 s and 2.15 s, individually. [ABSTRACT FROM AUTHOR]

This paper presents a method to identify regions that make up features like holes, slots, pockets as well as interacting features in a three-dimensional mesh of a computer-aided design (CAD)/Engineering model. Feature recognition is an important area in the field of CAD/Engineering with applications in model retrieval, creating an analysis model by defeaturing of the designed model for finite element applications, etc. Most feature recognition methods use either a cluster-based decomposition or feature line extraction through solid angles or curvature values, followed by graph-based heuristics. Such approaches require a user parameter for clustering or a threshold value for angle/curvature, neither of which is an easily deterministic one. The proposed algorithm identifies the features using contours generated by random cutting planes, followed by graph traversals (and not using heuristics) and without using parameter/threshold values. The algorithm can identify blind holes, through holes, slots and pockets. The geometry of most of the extracted features has also been identified using Gauss map. Interacting features have also been extracted and separated, which normally pose difficulty for most algorithms. Extensive experiments on CAD models from various benchmarks show that the algorithm is robust. Comparison with different algorithms (of which code was available) shows that our approach performs admirably and in the case of interacting features, the algorithm performs better than the existing ones. [ABSTRACT FROM AUTHOR]

The problem of determining visibility locations (VLs) on/inside a domain bounded by a planar C 1 -continuous curve (without vertices), such that entire domain is covered, is discussed in this paper. The curved boundary has been used without being approximated into lines or polygons. Initially, a few observations regarding the VLs for a curved boundary have been made. It is proposed that the set of VLs required to cover the domain be placed in a manner that the VLs and the lines connecting them form a spanning tree. Along with other observations, an algorithm has been provided which gives a near optimal number of VLs. The obtained number of VLs is then compared with a visibility disjoint set, called as witness points, to obtain a measure of the ‘nearness’ of the number of VLs to the optimum. The experiments on different curved shapes illustrate that the algorithm captures the optimal solution for many shapes and near-optimal for most others. [ABSTRACT FROM AUTHOR]

Haptic technologies allow for adding a new “touching” modality into virtual scenes. 3D reconstruction of a real life scene results, however, often in millions of polygons which cannot be simultaneously visualized and haptically rendered. In this paper, we propose a way of haptic interaction with real life scenes where multiple original images of the real scenes are augmented with reconstructed polygon meshes. We present our solution to the problems of haptic model alignment with the images and interactive haptic rendering of large polygon meshes with reconstruction artifacts. In particular, the presented collision detection algorithm is not restricted by any hypothesis and robust enough to support smooth interaction with millions of polygons. The feasibility and usability of the proposed solution is evaluated in a user study. [ABSTRACT FROM AUTHOR]

State-of-the-art approaches for tree reconstruction either put limiting constraints on the input side (requiring multiple photographs, a scanned point cloud or intensive user input) or provide a representation only suitable for front views of the tree. In this paper we present a complete pipeline for synthesizing and rendering detailed trees from a single photograph with minimal user effort. Since the overall shape and appearance of each tree is recovered from a single photograph of the tree crown, artists can benefit from georeferenced images to populate landscapes with native tree species. A key element of our approach is a compact representation of dense tree crowns through a radial distance map. Our first contribution is an automatic algorithm for generating such representations from a single exemplar image of a tree. We create a rough estimate of the crown shape by solving a thin-plate energy minimization problem, and then add detail through a simplified shape-from-shading approach. The use of seamless texture synthesis results in an image-based representation that can be rendered from arbitrary view directions at different levels of detail. Distant trees benefit from an output-sensitive algorithm inspired on relief mapping. For close-up trees we use a billboard cloud where leaflets are distributed inside the crown shape through a space colonization algorithm. In both cases our representation ensures efficient preservation of the crown shape. Major benefits of our approach include: it recovers the overall shape from a single tree image, involves no tree modeling knowledge and minimal authoring effort, and the associated image-based representation is easy to compress and thus suitable for network streaming. [ABSTRACT FROM AUTHOR]

This paper discusses the coincidence condition of two Bézier curves of the same degree, which is necessary for a curve/curve intersection algorithm. It proves that two Bézier curves of the same degree are coincident with each other if and only if they have a coincident control polygon or they can be reparameterized into the same non-reparameterizable Bézier curve of a lower degree. A simple method is also provided for detecting the reparameterizable case where a Bézier curve can be reparameterized into a non-reparameterizable one of a lower degree. [ABSTRACT FROM AUTHOR]

This paper proposes a distinct multiscale shape context (MSC) method for isometric 3D shape description and retrieval. For each feature point, a MSC descriptor is devised to capture the multiple spatial information on the basis of the intrinsic shape context, which is advantageous in solving the domain offset deficiency for intra-class shapes. Different from the traditional shape context method, the MSC descriptor is built based on the charts without angular bins and the shape distributions in local domains, which makes it not only simple but also efficient. To reduce the cost of shape representation, we detect a sparse set of feature points and design an improved bags-of-word model to encode the MSC descriptors. For retrieval improvement, an efficient while robust re-ranking algorithm by metric mapping is designed to alleviate the errors of the feature space. Finally, the experimental results have demonstrated significant performance gains on two public benchmarks. [ABSTRACT FROM AUTHOR]

In practice, a sampled vector field is viewed as a piecewise linear field, which simplifies the interpolation of curve integration, and this assumption is widely adopted in most visualization algorithms. However, existing works omit the local coherent nature of this simplification, which could be leveraged to improve the efficiency of computation. In this paper, we reformulate the scheme of linear interpolation and integration for the simplicial mesh grid with homogeneous coordinates, and find that we can benefit significantly by simultaneously integrating multiple curves passing through a single cell. Based on this observation, we revise the 4th-order Runge–Kutta method and propose an efficient cell-wise and step-wise batch advection scheme for both 2D and 3D datasets, which is useful in the multiple particle tracing for the integral curves, e.g. streamline, pathline, timeline and streakline. We apply our method to some applications for a series of datasets, and the results show that our batch advection method can significantly speed up the curve integration while comparing with the traditional 4th-order Runge–Kutta. [ABSTRACT FROM AUTHOR]

Video segmentation is an important preprocessing step for many computer vision and graphics tasks. Its main goal is to group the voxels in the video volume with similar appearance and motion into spatio-temporally consistent supervoxels. In this paper, we formulate video segmentation as an L 0 gradient minimization problem, so that the spatio-temporal coherence can be effectively enforced through a gradient sparsity pursuit way. In our method, the appearance and motion descriptor space is first built for over-segmented image patches of each video frame. Then the L 0 gradient minimization is performed in the descriptor space, for both spatial and temporal dimensions. To solve the non-convex L 0 norm minimization problem, we extend the fused coordinate descent algorithm from 2D image grids to 3D video volume. We conduct quantitative evaluation of our method in a public video segmentation benchmark LIBSVX. The experimental results demonstrate our superior performance to state-of-the-arts in segmentation accuracy and undersegmentation error, and comparable performance in boundary recall and explained variation. [ABSTRACT FROM AUTHOR]

567-meshes are a new type of closed and 2-manifold triangular meshes introduced by Aghdaii et al. in 2012 [1] . Vertices with valence less than 5 or greater than 7 are problematic for many mesh processing tasks such as edge collapse or surface subdivision. However, vertices with valence equal to 6 everywhere is most often impossible due to either surface topology or surface feature preservation, that is why 567-meshes are particularly of interest. This paper proposes a 567-remeshing algorithm that locally retriangulates the mesh considering vertex valence, vertex budget and mesh fidelity as a whole. This algorithm also offers the possibility to preserve a set of feature edges during remeshing. This results in a framework capable of low budget 567-remeshing where remeshed models have a much higher fidelity to the original surface compared to the state of the art. As applications of this work, we demonstrate that our remeshing improves the performances of mesh regularization and mesh connectivity compression. [ABSTRACT FROM AUTHOR]