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The physically based deformable curve models are widely used to simulate thin one-dimensional objects in computer graphics, interactive simulation, and surgery simulation. These models consider objects to be rods described by an adapted frame curve that contains the rod's centerline as well as the orthonormal material frame of each point on the centerline. However, they pose challenges including fine discretization, redundancy in modeling slender rods, and maintaining accuracy and stability. In this paper, we propose a novel physically based deformable B-spline curve model that regards curves as rods consisting of parallel fibers and derive elastic potential energy only from curves' representations. Therefore, our model does not take rotation-based adapted frames into consideration and reduces degree of freedom. Our model divides the curves into infinitesimal elements in parameter space and derives the analytical relationship between elastic potential energy function and curves' representations through the change of total length of infinitesimal elements' fibers. Our model can support material attributes in the real world and maintain the reality and stability of the solution. We employ isogeometric analysis to solve the dynamic equations derived from our deformable model as isogeometric analysis is suitable to solve the dynamic equations of parametric models. We compare the scenarios in the real world, our model's simulation results, and other model's results to demonstrate the reality of our models. The results are in line with expectation. We design several examples to demonstrate our models' applications. [ABSTRACT FROM AUTHOR]

The field of 3D craniofacial similarity calculation and craniofacial relationships(the relationships between the human skull and face) analysis is a challenging and meaningful task in archaeology, forensic science, and anthropology. Although anthropologists have been involved in the application and illustration of craniofacial relationships in their research, due to the complexity of the 3D skull (with multiple holes), and the facial expression changes of 3D human faces, it is difficult to accurately perform 3D craniofacial similarity calculations and theoretical validation of craniofacial relationships are difficult. To address this challenge, we propose a data-driven framework that constructs a shape feature space based on spectral analysis to describe the intrinsic structure of 3D skulls and faces. Our framework includes a shape analysis method to measure 3D craniofacial similarity and a statistical method using canonical correlation analysis to comprehensively describe the craniofacial relationships from global statistical features and individual geometric features. Based on an Asian craniofacial database, we demonstrate the effectiveness of our framework through validation results and skull identification. Most importantly, we provide two craniofacial relationships rules through theoretical validation and numerical results: R1-the human skull has a strong correlation with the face; R2-the similarity change trend of the skull is generally consistent with the corresponding face similarity. These craniofacial relationships rules can be applied to general craniofacial analysis tasks and scenarios, providing a solid theoretical basis for relevant researchers. Our research represents a significant contribution to the field of 3D craniofacial similarity calculation and craniofacial relationships analysis. [ABSTRACT FROM AUTHOR]

In 3D face analysis research, automated classification to recognize gender and ethnicity has received an increasing amount of attention in recent years. Feature extraction and feature calculation have a fundamental role in the process of classification construction. In particular, the challenge of 3D low-quality face data, including inconsistent mesh numbers or holes, makes it difficult to extract and calculate facial features. To overcome this challenge, we propose a shape descriptor Scaling invariant harmonic wave kernel signature (SIHWKS) that is robust to scaling, topology and sampling and can effectively describe the global and local properties of 3D shapes simultaneously by involving two energy parameters. We extract a local nose region in the center of the face using isogeodesic stripes replacing full facial information, which has a lower probability of occlusion and lower calculation complexity. Actually, the local nose region is constrained by the skull so that it has high distinction gender and ethnicity property and stability property that are robust to 3D facial expression for gender and ethnicity classification. Compared with gender and ethnicity classification based on 2D deep-learning methods influenced by texture information, the proposed method does not require complex processes for model training and only considers the geometric information of the 3D nose region. In addition, to estimate the effectiveness of our point descriptor SIHWKS for gender and ethnicity classification, we compare our SIHWKS with four existing descriptors – global point signature (GPS), heat kernel signature (HKS), wave kernel signature (WKS) and harmonic wave kernel signature (HWKS) – on four databases, namely, FRGC2.0, Bosphorus3D, Facewarehouse and Asian Mongolian craniofacial. Finally, we perform experiments comparing our method with other recent existing classification methods. The experimental results show that our proposed method can achieve a higher accuracy rate for gender and ethnicity classification. [ABSTRACT FROM AUTHOR]

We present an effective spectral matching method based on a shape association graph for finding region correspondences between two cel animation keyframes. We formulate the correspondence problem as an adapted quadratic assignment problem, which comprehensively considers both the intrinsic geometric and topology of regions to find the globally optimal correspondence. To simultaneously represent the geometric and topological similarities between regions, we propose a shape association graph (SAG), whose node attributes indicate the geometric distance between regions, and whose edge attributes indicate the topological distance between combined region pairs. We convert topological distance to geometric distance between geometric objects with topological features of the pairs, and introduce Kendall shape space to calculate the intrinsic geometric distance. By utilizing the spectral properties of the affinity matrix induced by the SAG, our approach can efficiently extract globally optimal region correspondences, even if shapes have inconsistent topology and severe deformation. It is also robust to shapes undergoing similarity transformations, and compatible with parallel computing techniques. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) is an advanced magnetic resonance technology that describes subtle brain structures using a diffusion tensor at each point. The obtained DTI image is always degraded since diffusion-weighted imaging sequences, which are used to estimate DTI images, are corrupted by noise. In this paper, we propose an approach called geometric invariant nonlocal means on the tensor manifold (GINLM-TM) to reduce undesired components in the degraded DTI image. We transform the diffusion tensor into a positive definite matrix (called a tensor) to measure the intrinsic property of the diffusion tensor. Then, we directly regularise DTI images in the tensor manifold endowed with an affine invariant metric. Finally, geometrically invariant measures of patches of tensors are used to define the similarity function of patches to ensure the similarity between patches is more accurate and robust. It is experimentally demonstrated that the proposed method performs adequately in reducing undesired components without blurring the boundaries of DTI images. The results of fractional anisotropy (FA) images and fibre tracking of our restored data indicate that our method performs well in denoising the DTI image. [ABSTRACT FROM AUTHOR]

The human mandible reconstruction is widely used in medical cosmetology, criminal investigation, archaeology and anthropology. This study is devoted to rapidly reconstructing 3D personalized mandibles, especially when the mandible is severely damaged or totally lost. An example-oriented method based on principal component analysis (PCA) is used to reconstruct the 3D shapes of mandibles. The predictor variable is an input cranium, while the response variables is a full mandible. The linear relationship between the cranium and mandible is obtained based on a number of skull samples, which is used as prior knowledge. The PCA method reduces the dimensionality of the skull data to improve the accuracy and speed of the reconstruction process. Experiments are conducted based on 215 skull models in the Chinese craniofacial database established in the study of craniofacial morphology informatics at Beijing Normal University. In our experiments, parameters are modified to help improve the reconstruction results. The proposed method exhibits higher accuracy than state-of-the-art methods according to comparison experiments results. Moreover, this method is robust to various types of input data and noise. Results indicate the proposed method is a fast and feasible tool for reconstructing 3D customized full mandibles. [ABSTRACT FROM AUTHOR]

Data centers, clusters, and grids have historically supported High-Performance Computing (HPC) applications. Due to the high capital and operational expenditures associated with such infrastructures, we have witnessed consistent efforts to run HPC applications in the cloud in the recent past. The potential advantages of this shift include higher scalability and lower costs. If, on the one hand, app instantiation—through customized Virtual Machines (VMs)—is a well-solved issue, on the other, the network still represents a significant bottleneck. When switching HPC applications to be executed on the cloud, we lose control of where VMs will be positioned and of the paths that will be traversed for processes to communicate with one another. To bridge this gap, we present Janus, a framework for dynamic, just-in-time path provisioning in cloud infrastructures. By leveraging emerging software-defined networking principles, the framework allows for an HPC application, once deployed, to have interprocess communication paths configured upon usage based on least-used network links (instead of resorting to shortest, pre-computed paths). Janus is fully configurable to cope with different operating parameters and communication strategies, providing a rich ecosystem for application execution speed up. Through an extensive experimental evaluation, we provide evidence that the proposed framework can lead to significant gains regarding runtime. Moreover, we show what one can expect in terms of system overheads, providing essential insights on how better benefiting from Janus. [ABSTRACT FROM AUTHOR]

Reconstructing 3D face from sparse points is an ill-posed problem. While there already exits available solutions addressing this problem, to our knowledge, we propose a better-performed approach which can robustly reconstruct fine 3D face shape. Our method includes two modules: face model establishment based on probabilistic principal component analysis (PPCA) trained in an unsupervised manner to learn transformation between landmarks and point cloud in their low-dimensional representation, and 3D face reconstruction based on learned relation between them to reconstruct fine face shape. Overall, our method considers the probability of face shape and learns more useful information of 3D face shape. We compare our method with 3 typical and state-of-the-art methods on 2 datasets and the effectiveness of our method is demonstrated generally. Further experiments on datasets with noise of different intensities show the stability of our method. [ABSTRACT FROM AUTHOR]

Among other aspects like attention and focus, the effectiveness of actions, such as training in percussion, also relies on the correct gesture and strength of the individual carrying out the activity repetitively to develop proper muscle memory and train motor skills. To make this process economical and efficient, we propose a system that models the feature of direction and strength of a tap and receives the corresponding active haptic feedback in an immersive virtual environment. We propose a novel tapping gesture model that takes electromyogram and vibration feedback into consideration. We also propose an approach of designing vibration modes that follow the mechanical stimulation principles and generate distinguishable vibration feedback with low-fidelity actuators. We developed a prototype using myoelectric and haptic apparatus (Myo armband and HTC VIVE controllers) and evaluated our system by conducting a user study with 50 participants. The evaluation shows that the users can distinguish three common materials (wood, rubber, and aluminum), and our system allows them to actively adjust their direction and strength to grasp the correct point while tapping. We demonstrate the efficacy of our tapping model on a virtual Chinese chimes application and observe positive feedback from both novices and expert users. [ABSTRACT FROM AUTHOR]

Research regarding the similarity measurements of 3D craniofacial models (including 3D skull and face models) is an important research direction in fields such as archaeology, forensic science, and anthropology and represents a meaningful and challenging task. Its major challenges are the fact that 3D skulls are geometric models with multiple holes and complex topologies, there are facial expression changes on the 3D faces. Therefore, the general 3D shape similarity measurements, which are sensitive to boundaries and expression changes, make it impossible to simultaneously measure skull and face similarity. In this paper, we define a 3D signature to describe the pure intrinsic structure and distinguish the similar basic shape and complex topology of 3D skulls and faces: the harmonic wave kernel signature (HWKS). The HWKS is a point descriptor involving the Laplace–Beltrami operator, which is able to effectively extract geometrical and topological information from 3D skulls and faces. Based on the HWKS, we provide an effective pipeline for 3D skull and face similarity measurement by calculating the cosine distance between the HWKS values of 3D skulls and faces. By making comparisons with the wave kernel signature, the HWKS simultaneously describes both local and global properties of a shape. Results from a number of experiments have already shown that our framework is suitable for both measure 3D skull similarity and face similarity, and more importantly, measuring skull similarity and face similarity are two independent processes although using the same framework. By using the same measurement method for 3D skull similarity and face similarity, we observe an effective craniofacial relationship under unified metrics: The change rate of skull similarity is generally consistent with the corresponding face similarity, indicating the correlation between the shape of the 3D skull and its corresponding 3D face shape. And our experimental results show the rationality and effectiveness of this method, which refers to the previous researchers measure the similarity of the reconstructed face from the original skull to reflect the similarity of the original skull. [ABSTRACT FROM AUTHOR]

3D non-rigid shape similarity is a meaningful and challenging task in deformable shape analysis. In this paper, we present a 3D non-rigid shape similarity measure framework based on Laplace-Beltrami operator which achieves the state-of-the-art performance in shape analysis tasks. The presented framework is used to measure 3D non-rigid shape similarity by calculating the Fréchet distance between the shape spectral distances distribution curves extracting geometry and topology information of shapes. Here, the wave diffusion distance within shape spectral distances is selected because it can describe the shape with high accuracy and does not depend on the time parameter. In addition, our framework is more flexible and computationally efficient: it can be generalized to any distance distribution curves and different distances between the shape distances distribution curves. Experiment results show that the proposed framework can measure 3D non-rigid shape similarity accurately and robustly on benchmarks and have good performance in 3D non-rigid shape retrieval. [ABSTRACT FROM AUTHOR]

We introduce a 2D vectorized shape correspondence method based on Kendall shape space and region adjacency graph. We regard shape correspondence in 2D animation as a weighted bipartite graph matching problem and optimize it by means of various weights, including geometric attribute, local topological information, and global topological information in 2D animation drawing. The measuring method in Kendall shape space is introduced to determine similarity between two regions and a local adjacent region matching method is presented to associate the vicinity of the corresponding region by utilizing local topology information. Ultimately, we propose a globally optimal shape matching method, which exploits the global topological information to get the final result of the shape correspondence. Our approach can efficiently match associated regions that have exaggerated deformation and unstable topology between two shapes in 2D animation. It is also robust to the similarity transformation of shapes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel framework for 3D facial similarity measures and facial data organization. The 3D facial similarity measures of our method are based on iso-geodesic stripes and conformal parameterization. Using the conformal parameterization, the 3D facial surface can be mapped into a 2D domain and the iso-geodesic stripes of the face can be measured. The measure results can be regarded as the similarity of faces, which is robust to head poses and facial expressions. Based on the measure result, a hierarchical structure of faces can be constructed, which is used to organize different faces. The structure can be utilized to accelerate the face searching speed in a large database. In experiment, we construct the hierarchical structures from two public facial databases: Gavab and Texas3D. The searching speed based on the structure can be increased by 4-6 times without accuracy loss of recognition. [ABSTRACT FROM AUTHOR]

Purpose: Virtual digital resources and printed models have become indispensable tools for medical training and surgical planning. Nevertheless, printed models of soft tissue organs are still challenging to reproduce. This study adopts open source packages and a low-cost desktop 3D printer to convert multiple modalities of medical images to digital resources (volume rendering images and digital models) and lifelike printed models, which are useful to enhance our understanding of the geometric structure and complex spatial nature of anatomical organs. Materials and methods: Neuroimaging technologies such as CT, CTA, MRI, and TOF-MRA collect serial medical images. The procedures for producing digital resources can be divided into volume rendering and medical image reconstruction. To verify the accuracy of reconstruction, this study presents qualitative and quantitative assessments. Subsequently, digital models are archived as stereolithography format files and imported to the bundled software of the 3D printer. The printed models are produced using polylactide filament materials. Results: We have successfully converted multiple modalities of medical images to digital resources and printed models for both hard organs (cranial base and tooth) and soft tissue organs (brain, blood vessels of the brain, the heart chambers and vessel lumen, and pituitary tumor). Multiple digital resources and printed models were provided to illustrate the anatomical relationship between organs and complicated surrounding structures. Three-dimensional printing (3DP) is a powerful tool to produce lifelike and tangible models. Conclusions: We present an available and cost-effective method for producing both digital resources and printed models. The choice of modality in medical images and the processing approach is important when reproducing soft tissue organs models. The accuracy of the printed model is determined by the quality of organ models and 3DP. With the ongoing improvement of printing techniques and the variety of materials available, 3DP will become an indispensable tool in medical training and surgical planning. [ABSTRACT FROM AUTHOR]

This paper presents a novel base-points-driven shape correspondence (BSC) approach to extract skeletons of articulated objects from 3D mesh shapes. The skeleton extraction based on BSC approach is more accurate than the traditional direct skeleton extraction methods. Since 3D shapes provide more geometric information, BSC offers the consistent information between the source shape and the target shapes. In this paper, we first extract the skeleton from a template shape such as the source shape automatically. Then, the skeletons of the target shapes of different poses are generated based on the correspondence relationship with source shape. The accuracy of the proposed method is demonstrated by presenting a comprehensive performance evaluation on multiple benchmark datasets. The results of the proposed approach can be applied to various applications such as skeleton-driven animation, shape segmentation and human motion analysis. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel region-based active contour model based on global intensity fitting energy in a variational level set framework. Meanwhile, an internal energy term is introduced, and it forces the level set function to be close to a signed distance function. Image global information utilized efficiently makes the proposed model insensitive to noise, and the introduced penalty term can avoid the costly re-initialization for the evolving level set function, which not only speeds up the contour evolvement, but also improves accuracy of the final contour. Comparisons with other classical region-based models, such as Chan-Vese model and Region-Scalable Fitting (RSF) model, show the advantages of our model in terms of efficiency and accuracy. Moreover, the model is robust to noise. [ABSTRACT FROM AUTHOR]