30 results
Search Results
2. ASSESSMENT OF 3D MESH WATERMARKING TECHNIQUES.
- Author
-
Sharma, Neha and Panda, Jeebananda
- Abstract
With the increasing usage of three-dimensional meshes in Computer-Aided Design (CAD), medical imaging, and entertainment fields like virtual reality, etc., the authentication problems and awareness of intellectual property protection have risen over the last decade. Numerous watermarking schemes have been suggested to protect ownership and prevent the threat of data piracy. This paper begins with the potential difficulties that arose when dealing with three-dimension entities in comparison to two-dimensional entities and also lists possible algorithms suggested hitherto and their comprehensive analysis. Attacks, also play a crucial role in deciding on a watermarking algorithm so an attack based analysis is also presented to analyze the resilience of watermarking algorithms under several attacks. In the end, some evaluation measures and potential solutions are brooded over to design robust and oblivious watermarking schemes in the future. [ABSTRACT FROM AUTHOR]
- Published
- 2022
3. 3D hand pose and shape estimation from monocular RGB via efficient 2D cues.
- Author
-
Zhang, Fenghao, Zhao, Lin, Li, Shengling, Su, Wanjuan, Liu, Liman, and Tao, Wenbing
- Subjects
JOINTS (Anatomy) ,MONOCULARS ,DEEP learning - Abstract
Estimating 3D hand shape from a single-view RGB image is important for many applications. However, the diversity of hand shapes and postures, depth ambiguity, and occlusion may result in pose errors and noisy hand meshes. Making full use of 2D cues such as 2D pose can effectively improve the quality of 3D human hand shape estimation. In this paper, we use 2D joint heatmaps to obtain spatial details for robust pose estimation. We also introduce a depth-independent 2D mesh to avoid depth ambiguity in mesh regression for efficient hand-image alignment. Our method has four cascaded stages: 2D cue extraction, pose feature encoding, initial reconstruction, and reconstruction refinement. Specifically, we first encode the image to determine semantic features during 2D cue extraction; this is also used to predict hand joints and for segmentation. Then, during the pose feature encoding stage, we use a hand joints encoder to learn spatial information from the joint heatmaps. Next, a coarse 3D hand mesh and 2D mesh are obtained in the initial reconstruction step; a mesh squeeze-and-excitation block is used to fuse different hand features to enhance perception of 3D hand structures. Finally, a global mesh refinement stage learns non-local relations between vertices of the hand mesh from the predicted 2D mesh, to predict an offset hand mesh to fine-tune the reconstruction results. Quantitative and qualitative results on the FreiHAND benchmark dataset demonstrate that our approach achieves state-of-the-art performance. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
4. Reverse engineering from 3D mesh to ceramic product in the form of miranda kerr tea for one teapot in PT doulton Indonesia.
- Author
-
Anggoro, P.W., Tan Wijaya, A.R., Yuniarto, T., Bayuseno, A.P., Jamari, J., Tauviqirrahman, M., and Setyohadi, D.B.
- Subjects
REVERSE engineering ,STEREOLITHOGRAPHY ,TEAPOTS ,COMPUTER-aided engineering ,NUMERICAL control of machine tools ,ENGINEERING systems - Abstract
The design and manufacturing strategy using reverse engineering (RE) for Miranda Kerr Tea for One Teapot are presented in this paper. A computer-aided reverse engineering system (CARE System) was applied to minimize file errors generated by scanning Miranda Kerr Tea for One Teapot sample products made from Bone China clay. Digital data from the scanning process is used to design a teapot model that is precise and accurate. The digital data generated by Next Engine 3D and the priXa 1588 CMM is then converted into stereolithography (STL) file format (triangle-based data). The process of making 3D CAD models consists of: editing the 3D mesh from the scanning results, 3D CAD design forming the size of the fire, the size of the model, and the 3D CAD milling process using PowerSHAPE with the final result in the form of the surface of each part of the Teapot product. Manufacturing optimization to get the optimal machining strategy used PowerMILL and CNC machines. The casting process becomes a follow-up process after machining the mold of the designed product. This research has succeeded in demonstrating the advantages of using CARE System technology in the national ceramic industry in Indonesia so that it can compete at national and international levels. This is based on the magnitude of the RE error value of less than 1.00 mm with a total processing time of 43 hours 18 minutes 10 seconds and a total cost of about $ 4172.35. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
5. A FAST METHOD FOR MEASURING THE SIMILARITY BETWEEN 3D MODEL AND 3D POINT CLOUD.
- Author
-
Zongliang Zhang, Jonathan Li, Xin Li, Yangbin Lin, Shanxin Zhang, and Cheng Wang
- Subjects
THREE-dimensional modeling ,CLOUD computing - Abstract
This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
6. Pixel-level block classification and crack detection from 3D reconstruction models of masonry structures using convolutional neural networks.
- Author
-
Loverdos, Dimitrios and Sarhosis, Vasilis
- Subjects
- *
CONVOLUTIONAL neural networks , *WOODEN beams , *MASONRY , *ENGINEERS , *BRIDGE testing , *ARCH bridges - Abstract
Inspection and documentation of masonry structures is a time-consuming and expensive process that heavily relies on an engineer's expertise. This paper introduces a computer vision-based method that automates the creation of classified point clouds from 3D reconstruction models obtained through photogrammetry and/or laser scanning. By leveraging Convolutional Neural Networks (CNN) on 3D renders, the proposed methodology can be used to classify structural features (i.e., blocks, mortar, cracks) with greater accuracy and less effort than conventional methods. Moreover, this approach is flexible and can include further classifications by incorporating additional CNN models, allowing broader applications across various materials (i.e., concrete, steel, timber) and defects. Additionally, a precise methodology for accurate crack quantification featuring a manual annotation tool was introduced which was validated using outputs from a full-scale masonry arch bridge test carried out in the laboratory. The results emphasize the robustness of the classification approach and highlight the useful geometric information that can be gained from full-scale masonry structures. The proposed approach has the potential to use image data from UAVs/static cameras and revolutionize the way we document and inspect structures in the future. • Classification of 3D point-cloud of masonry fabric via semantic-segmentation on reality-mesh models. • Automatic detection of cracks from 3D reconstruction models of masonry structures • Quantification of the extend of detected cracks in 3D space. • Comparison of 3D photogrammetry software using a case study of an experimental masonry arch bridge. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
7. ANALYSIS OF 3D BUILDING MODELS ACCURACY BASED ON THE AIRBORNE LASER SCANNING POINT CLOUDS.
- Author
-
Ostrowski, W., Pilarska, M., Charyton, J., and Bakuła, K.
- Subjects
AIRBORNE lasers ,THREE-dimensional imaging ,CLOUD computing - Abstract
Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term “3D building models" can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
8. 3D hand pose and shape estimation from monocular RGB via efficient 2D cues
- Author
-
Fenghao Zhang, Lin Zhao, Shengling Li, Wanjuan Su, Liman Liu, and Wenbing Tao
- Subjects
hand ,3D reconstruction ,deep learning ,image features ,3D mesh ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Abstract Estimating 3D hand shape from a single-view RGB image is important for many applications. However, the diversity of hand shapes and postures, depth ambiguity, and occlusion may result in pose errors and noisy hand meshes. Making full use of 2D cues such as 2D pose can effectively improve the quality of 3D human hand shape estimation. In this paper, we use 2D joint heatmaps to obtain spatial details for robust pose estimation. We also introduce a depth-independent 2D mesh to avoid depth ambiguity in mesh regression for efficient hand-image alignment. Our method has four cascaded stages: 2D cue extraction, pose feature encoding, initial reconstruction, and reconstruction refinement. Specifically, we first encode the image to determine semantic features during 2D cue extraction; this is also used to predict hand joints and for segmentation. Then, during the pose feature encoding stage, we use a hand joints encoder to learn spatial information from the joint heatmaps. Next, a coarse 3D hand mesh and 2D mesh are obtained in the initial reconstruction step; a mesh squeeze-and-excitation block is used to fuse different hand features to enhance perception of 3D hand structures. Finally, a global mesh refinement stage learns non-local relations between vertices of the hand mesh from the predicted 2D mesh, to predict an offset hand mesh to fine-tune the reconstruction results. Quantitative and qualitative results on the FreiHAND benchmark dataset demonstrate that our approach achieves state-of-the-art performance.
- Published
- 2023
- Full Text
- View/download PDF
9. Segmentation of 3D Meshes Usingp-Spectral Clustering.
- Author
-
Chahhou, Mohamed, Moumoun, Lahcen, Far, Mohamed El, and Gadi, Taoufiq
- Subjects
IMAGE segmentation ,DIGITAL image processing ,MESH networks ,THREE-dimensional display systems ,COGNITIVE science - Abstract
In this paper, we propose a new approach to get the optimal segmentation of a 3D mesh as a human can perceive using the minima rule and spectral clustering. This method is fully unsupervised and provides a hierarchical segmentation via recursive cuts. We introduce a new concept of the adjacency matrix based on cognitive studies. We also introduce the use of one-spectral clustering which leads to the optimal Cheeger cut value. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
- View/download PDF
10. Estimación por método UPD multivariable de un modelo óptimo 3D de recursos eoloenergético.
- Author
-
Terrero-Matos, Eduardo and Legrá-Lobaina, Arístides A.
- Subjects
- *
WIND power , *MATHEMATICAL models , *MATHEMATICAL optimization , *WEIBULL distribution , *STATISTICAL sampling - Abstract
This paper presents a multivariate UPD estimator, family member [A,U,T] with parameters p and s, which allows to calculate simultaneously parameters of Weibull K and C at a point Pe from the measured values of these variables in several sampling points. During the 3D estimation, the spatial relationship between the data and the associated values of elevation and roughness of the terrain is taken into account; with the estimated results, a model of wind energy resources is developed, given by a 3D mesh where to each node is associated the values of K and C. Finally, a method of combinatory optimization is described to find the values of p and s such that the mesh model is feasible and optimal for the given data. [ABSTRACT FROM AUTHOR]
- Published
- 2020
11. TPNet: A novel mesh analysis method via topology preservation and perception enhancement.
- Author
-
Li, Peifang, He, Fazhi, Fan, Bo, and Song, Yupeng
- Subjects
- *
ARTIFICIAL neural networks , *DATA structures , *CONVOLUTIONAL neural networks , *MESH networks , *MATHEMATICAL convolutions , *COMPUTER graphics - Abstract
3D polygon mesh is an important and popular representation of 3D shapes in the field of computer graphics and computer-aided design. Recent works have introduced deep neural networks for mesh data analysis. However, it remains a great challenge for convolutional neural networks to learn mesh shape effectively due to the difficulty of deriving long-range information from the irregular data structure. Another tricky problem is how to explore a high effective representation of the input feature for mesh learning network. In this paper, we propose a novel 3D mesh learning method, named TPNet, which enhances the perception and learns long-range information by customizing dilated convolution for non-uniform mesh data. Specifically, we devise a faithful strategy that accurately locates the position where dilated convolutions can be adopted, despite the non-uniformity and irregularity of the mesh data. Furthermore, our method proposes a topology-preserved 7-dimension feature representation for mesh data and aggregates the features via stacks of convolution layers and dilated convolution layers. Extensive experiments demonstrate the effectiveness of our approach on 3D mesh learning tasks, where we show superior or at least comparable performance to the SOTA approaches. • This work is the first to extend dilated convolution to edges for non-uniform mesh data. • Dilated convolution on mesh edges enhances the perception without increasing computation costs. • We explore the characteristics of 3D mesh and propose a topology-preserved edge feature. • Our TPNet achieves superior or at least comparable performance to SOTA methods. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
12. 3D building model generation from MLS point cloud and 3D mesh using multi-source data fusion
- Author
-
Weiquan Liu, Yu Zang, Zhangyue Xiong, Xuesheng Bian, Chenglu Wen, Xiaolei Lu, Cheng Wang, José Marcato, Junior, Wesley Nunes Gonçalves, and Jonathan Li
- Subjects
3D building model generation ,MLS point cloud ,3D mesh ,Multi-source data fusion ,Physical geography ,GB3-5030 ,Environmental sciences ,GE1-350 - Abstract
The high-precision generation of 3D building models is a controversial research topic in the field of smart cities. However, due to the limitations of single-source data, existing methods cannot simultaneously balance the local accuracy, overall integrity, and data scale of the building model. In this paper, we propose a novel 3D building model generation method based on multi-source 3D data fusion of 3D point cloud data and 3D mesh data with deep learning method. First, A Multi-Source 3D data Quality Evaluation Network (MS3DQE-Net) is proposed for evaluating the quality of 3D meshes and 3D point clouds. Then, the evaluation results are utilized to guide 3D building model generation. The MS3DQE-Net uses 3D meshes and 3D point clouds as inputs and fuses the learned features to obtain a more complete shape description. To train MS3DQE-Net, a multi-source 3D dataset is constructed, which collected from a real scene based on mobile laser scanning (MLS) 3D point clouds and 3D mesh data, including pairs of matching 3D meshes and 3D point clouds of the 3D building model. Specifically, to our knowledge, we are the first researchers to propose such multi-source 3D dataset. The experimental results show that MS3DQE-Net achieves a state-of-the-art performance in multi-source 3D data quality evaluation. We demonstrate the large-scale and high-precision, 3D building model generation approach on a campus.
- Published
- 2023
- Full Text
- View/download PDF
13. D3AdvM: A direct 3D adversarial sample attack inside mesh data.
- Author
-
Xu, Huangxinxin, He, Fazhi, Fan, Linkun, and Bai, Junwei
- Subjects
- *
ARTIFICIAL neural networks , *DEEP learning , *ENGINEERING design , *ARTIFICIAL intelligence , *MESH networks , *APPROXIMATION error - Abstract
Deep learning and neural networks are being extended to geometric design and computation. Recent studies show that deep neural networks are vulnerable to adversarial samples. However, for 3D mesh adversarial samples, the most related studies actually attack the 2D victim networks, in which they have to project 3D objects to 2D images. In this paper, we present D3AdvM (Direct 3D adversary for mesh) to directly generate adversarial samples inside mesh data. Specifically, we propose two adversary generation approaches: vertex-based and edge-based. The first one, 3DVP (3D Vertex-based Perturbation), skillfully searches the optimized vertices positions based on opposite gradient fitness. The second one, KES (Key Edge-based Selection), carefully collapses the key feature edges according to importance of edge feature. Thus, our approaches avoid 3D/2D projections and approximation errors. Also, our approach can reduce the computation overhead. In addition, the proposed D3AdvM can control the number of perturbed vertices for real-world engineering designs and applications. Extensive experiments show that the generated 3D meshes are effective to attack classification networks. Furthermore, we evaluate the transferability, in which D3AdvM can attack both mesh-based networks and point cloud-based networks as victim networks. Our findings could benefit 3D geometry design based on the new generation of artificial intelligence and big data. • This work is the first one to directly attack mesh-based neural networks with adversarial meshes in 3D space without the 2D projection. • We explore the characteristics of 3D mesh topological entities and propose both vertex-based and edge-based adversarial approaches. • D3AdvM can constrain the adversarial samples within a specific number to support high feasibility in real-world applications. • D3AdvM shows valuable transferability to attack different versions of mesh-based networks and even the point cloud-based networks. • Our findings could benefit 3D geometry design based on the new generation of artificial intelligence and big data. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
14. LOFT: A low-overhead fault-tolerant routing scheme for 3D NoCs.
- Author
-
Zhou, Jun, Li, Huawei, Wang, Tiancheng, and Li, Xiaowei
- Subjects
- *
FAULT tolerance (Engineering) , *SYSTEMS on a chip , *INTEGRATED circuits , *PERFORMANCE evaluation , *ROUTING (Computer network management) - Abstract
As one of the main trends of communication technology for 3D integrated circuits, the 3D networks-on-chip (NoCs) have drawn high concern from the academia. The links are main components of the NoCs. For the permanent link faults, the fault-tolerant routing scheme has been regarded as an effective mechanism to ensure the performance of the 2D NoCs. In this paper, we propose a low-overhead fault-tolerant routing scheme called LOFT for 3D Mesh NoCs without requiring any virtual channels (VCs). LOFT is a deadlock-free scheme by adopting a logic-based routing named LBDRe 2 guided by a turn model Complete-OE. The experimental results show that LOFT possesses better performance, improved reliability and lower overhead compared with the state-of-the-art reliable routing schemes. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
15. Primary Orbital Reconstruction with Selective Laser Melting (SLM) of Patient-Specific Implants (PSIs): An Overview of 96 Surgically Treated Patients.
- Author
-
Rana, Majeed, Moellmann, Henriette L., Schorn, Lara, Lommen, Julian, Rana, Madiha, Wilkat, Max, and Hufendiek, Karsten
- Subjects
SELECTIVE laser melting ,EYE-socket fractures ,INDUSTRIAL lasers ,ANALYSIS of colors ,BODY surface mapping ,KNOWLEDGE transfer - Abstract
Contemporary advances in technology have allowed the transfer of knowledge from industrial laser melting systems to surgery; such an approach could increase the degree of accuracy in orbital restoration. The aim of this study was to examine the accuracy of selective laser melted PSIs (patient-specific implants) and navigation in primary orbital reconstruction. Ninety-six patients with orbital fractures were included in this study. Planned vs. achieved orbital volumes (a) and angles (b) were compared to the unaffected side (n = 96). The analysis included the overlay of post-treatment on planned images (iPlan 3.0.5, Brainlab
® , Feldkirchen, Germany). The mean difference in orbital volume between the digitally planned orbit and the postoperative orbit was 29.16 cm3 (SD 3.54, presurgical) to 28.33 cm3 (SD 3.64, postsurgical, t = 5.00, df = 95.00; p < 0.001), resulting in a mean volume difference (planned vs. postop) of less than 1 cm3 . A 3D analysis of the color mapping showed minor deviations compared to the mirrored unaffected side. The results suggested that primary reconstruction in complex orbital wall fractures can be routinely achieved with a high degree of accuracy by using selective laser melted orbital PSIs. [ABSTRACT FROM AUTHOR]- Published
- 2022
- Full Text
- View/download PDF
16. Modeling of 3D Human Face for Tamil Visual Speech Synthesis.
- Author
-
Anantha Natarajan, V. and Jothilakshmi, S.
- Subjects
FACE ,HEARING impaired students ,RADIAL basis functions ,EDUCATION - Abstract
The visual equivalent of human face exhibiting articulatory expression of a unit of sound in spoken language is termed as Viseme. The Visemes can be used to teach hearing impaired students visually and effectively. In this paper a method to construct three dimensional human faces from a single 2D image is proposed. By this method a generic 3D mesh of human face is deformed using the calculated feature points from 2D images. The method consists of the following steps namely locate corresponding feature vertices in both 2D image and the generic 3D mesh, calculating the corresponding 3D co-ordinates of the 2D feature points and relative camera position and finally deforming the generic 3D mesh using the Radial Basis Function (RBF) based interpolation. Later the constructed three dimensional models can be animated by morphing different visemes together. The inner articulatory organs are modelled using Java3D and blended with these constructed 3D dimensional units. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
17. 3D mesh transformation preprocessing system in the real space for augmented reality services
- Author
-
Young-Suk Yoon, Sangwon Hwang, Dogyoon Lee, Sangyoun Lee, Jae-Won Suh, and Sung-Uk Jung
- Subjects
3D mesh ,3D point cloud ,3D point labeling ,AR service ,Information technology ,T58.5-58.64 - Abstract
We propose a preprocessing system that transforms the real world into 3D mesh virtual world to provide augmented reality (AR) services. The proposed system uses a monocular RGB camera to obtain sequential images to generate real space. First, we create 3D real-world space composed of point clouds using sequential color images. And then, we segment the objects in each color image and assign an identification number for each object. Also, we execute ‘3D point labeling’, which assigns identification numbers from 2D segmented object to 3D point cloud through a simple projection manner with several parameters. This process could collect 3D point cloud with same the label by as an object. Finally, only the 3D point clouds that have the same identification number by as an object are used to generate 3D mesh. This paper confirmed that 3D mesh could be created using the only general monocular camera without the help of special 3D sensors.
- Published
- 2021
- Full Text
- View/download PDF
18. Mesh resizing based on hierarchical saliency detection.
- Author
-
Jia, Shixiang, Zhang, Caiming, Li, Xuemei, and Zhou, Yuanfeng
- Subjects
NONLINEAR theories ,MATHEMATICAL functions ,DESCRIPTOR systems ,MESH networks ,MATHEMATICAL analysis - Abstract
Abstract: Mesh saliency is a perception-inspired metric for regional importance which is helpful to many aspects of mesh processing. However, existing mesh saliency cannot be used in mesh resizing directly because of the neglect of resizing direction. In this paper, we propose a region descriptor based on its vulnerability to a resizing direction, and use this descriptor to compute the region’s saliency based on its contrast to neighboring regions. In order to avoid being misled by repeated small-scale features on the mesh, we put forward a hierarchical method for saliency computing. We build a hierarchical coarse-to-fine segmentations of the input mesh, and evaluate the saliency value on different levels of segmentations. Finally these saliency values are integrated into one saliency map after applying non-linear suppression. Equipped with the saliency map, a framework for non-homogeneous mesh resizing is presented. We regard every edge as a spring, and scale the mesh by stretching the edge. Based on the salience value, we build a global energy function on the mesh. Experiments show that our resizing method based on hierarchical saliency analysis can produce visually appealing results. [Copyright &y& Elsevier]
- Published
- 2014
- Full Text
- View/download PDF
19. Study on Automatic 3D Facial Caricaturization: From Rules to Deep Learning
- Author
-
Nicolas Olivier, Glenn Kerbiriou, Ferran Arguelaguet, Quentin Avril, Fabien Danieau, Philippe Guillotel, Ludovic Hoyet, and Franck Multon
- Subjects
caricature ,style transfer ,machine learning ,geometry processing ,3D mesh ,perceptual study ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Facial caricature is the art of drawing faces in an exaggerated way to convey emotions such as humor or sarcasm. Automatic caricaturization has been explored both in the 2D and 3D domain. In this paper, we propose two novel approaches to automatically caricaturize input facial scans, filling gaps in the literature in terms of user-control, caricature style transfer, and exploring the use of deep learning for 3D mesh caricaturization. The first approach is a gradient-based differential deformation approach with data driven stylization. It is a combination of two deformation processes: facial curvature and proportions exaggeration. The second approach is a GAN for unpaired face-scan-to-3D-caricature translation. We leverage existing facial and caricature datasets, along with recent domain-to-domain translation methods and 3D convolutional operators, to learn to caricaturize 3D facial scans in an unsupervised way. To evaluate and compare these two novel approaches with the state of the art, we conducted the first user study of facial mesh caricaturization techniques, with 49 participants. It highlights the subjectivity of the caricature perception and the complementarity of the methods. Finally, we provide insights for automatically generating caricaturized 3D facial mesh.
- Published
- 2022
- Full Text
- View/download PDF
20. Reverse engineering from 3D mesh to ceramic product in the form of miranda kerr tea for one teapot in PT doulton Indonesia
- Author
-
P.W. Anggoro, A.R. Tan Wijaya, T. Yuniarto, A.P. Bayuseno, J. Jamari, M. Tauviqirrahman, and D.B. Setyohadi
- Subjects
miranda kerr tea for one teapot ,re ,cmm ,3d scanner ,3d mesh ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
The design and manufacturing strategy using reverse engineering (RE) for Miranda Kerr Tea for One Teapot are presented in this paper. A computer-aided reverse engineering system (CARE System) was applied to minimize file errors generated by scanning Miranda Kerr Tea for One Teapot sample products made from Bone China clay. Digital data from the scanning process is used to design a teapot model that is precise and accurate. The digital data generated by Next Engine 3D and the priXa 1588 CMM is then converted into stereolithography (STL) file format (triangle-based data). The process of making 3D CAD models consists of: editing the 3D mesh from the scanning results, 3D CAD design forming the size of the fire, the size of the model, and the 3D CAD milling process using PowerSHAPE with the final result in the form of the surface of each part of the Teapot product. Manufacturing optimization to get the optimal machining strategy used PowerMILL and CNC machines. The casting process becomes a follow-up process after machining the mold of the designed product. This research has succeeded in demonstrating the advantages of using CARE System technology in the national ceramic industry in Indonesia so that it can compete at national and international levels. This is based on the magnitude of the RE error value of less than 1.00 mm with a total processing time of 43 hours 18 minutes 10 seconds and a total cost of about $ 4172.35.
- Published
- 2021
- Full Text
- View/download PDF
21. Generation of 3D Tumor Models from DICOM Images for Virtual Planning of its Recession.
- Author
-
Rodríguez-Bastidas, Oscar and Vargas-Rosero, Hermes-Fabián
- Subjects
IMAGE segmentation ,MAGNETIC resonance imaging ,DIAGNOSTIC imaging ,DIGITAL images ,VIRTUAL reality - Abstract
Copyright of Revista Facultad de Ingeniería - UPTC is the property of Universidad Pedagogica y Tecnologica de Colombia, Facultad de Ingenieria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2020
- Full Text
- View/download PDF
22. 3D mesh transformation preprocessing system in the real space for augmented reality services
- Author
-
Sangwon Hwang, Sung-Uk Jung, Jae-Won Suh, Young-Suk Yoon, Dogyoon Lee, and Sangyoun Lee
- Subjects
Computer Networks and Communications ,Computer science ,Point cloud ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,Projection (mathematics) ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,Point (geometry) ,Polygon mesh ,Computer vision ,3D point labeling ,lcsh:T58.5-58.64 ,Color image ,business.industry ,lcsh:Information technology ,020208 electrical & electronic engineering ,020206 networking & telecommunications ,Object (computer science) ,3D point cloud ,Hardware and Architecture ,RGB color model ,Augmented reality ,AR service ,Artificial intelligence ,business ,3D mesh ,Software ,Information Systems - Abstract
We propose a preprocessing system that transforms the real world into 3D mesh virtual world to provide augmented reality (AR) services. The proposed system uses a monocular RGB camera to obtain sequential images to generate real space. First, we create 3D real-world space composed of point clouds using sequential color images. And then, we segment the objects in each color image and assign an identification number for each object. Also, we execute ‘3D point labeling’, which assigns identification numbers from 2D segmented object to 3D point cloud through a simple projection manner with several parameters. This process could collect 3D point cloud with same the label by as an object. Finally, only the 3D point clouds that have the same identification number by as an object are used to generate 3D mesh. This paper confirmed that 3D mesh could be created using the only general monocular camera without the help of special 3D sensors.
- Published
- 2021
23. An end-to-end geometric deficiencies elimination algorithm for 3D meshes
- Author
-
Huijie Fan, Xu Tang, Bingtao Ma, Liangliang Nan, Yang Cong, and Hongsen Liu
- Subjects
Computer science ,Geometric deficiencies ,Outer product ,020207 software engineering ,02 engineering and technology ,Object (computer science) ,Tree (graph theory) ,Computer graphics ,Mesh repair ,3D Mesh ,Face (geometry) ,0202 electrical engineering, electronic engineering, information engineering ,Polygon mesh ,Representation (mathematics) ,Algorithm ,Geometric data analysis - Abstract
The 3D mesh is an important representation of geometric data. It is widely used in computer graphics and has attracted more attention in computer vision community recently. However, in the generation of mesh data, geometric deficiencies (e.g., duplicate elements, degenerate faces, isolated vertices, self-intersection, and inner faces) are unavoidable. Geometric deficiencies may violate the topology structure of an object and affect the use of 3D meshes. In this paper, we propose an end-to-end algorithm to eliminate geometric deficiencies effectively and efficiently for 3D meshes in a specific and reasonable order. Specifically, duplicate elements can be first eliminated by assessing appear times of vertices or faces. Then, degenerate faces can be removed according to the outer product of two edges. Next, since isolated vertices do not appear in any face vertices, they can be deleted directly. Afterward, self-intersecting faces are detected and remeshed by using an AABB tree. Finally, we detect and remove an inner face according to whether multiple random rays shooted from a face can reach infinity. Experiments on ModelNet40 dataset illustrate that our method can eliminate the deficiencies of 3D meshes thoroughly.
- Published
- 2021
24. Reverse engineering from 3D mesh to ceramic product in the form of miranda kerr tea for one teapot in PT doulton Indonesia
- Author
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Jamari Jamari, D.B. Setyohadi, Athanasius Priharyoto Bayuseno, T. Yuniarto, P.W. Anggoro, A.R. Tan Wijaya, and M. Tauviqirrahman
- Subjects
Reverse engineering ,Engineering ,General Computer Science ,business.industry ,General Chemical Engineering ,General Engineering ,Engineering (General). Civil engineering (General) ,computer.software_genre ,Manufacturing strategy ,visual_art ,Product (mathematics) ,visual_art.visual_art_medium ,re ,3d mesh ,Polygon mesh ,Ceramic ,miranda kerr tea for one teapot ,TA1-2040 ,Process engineering ,business ,3d scanner ,computer ,cmm ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
The design and manufacturing strategy using reverse engineering (RE) for Miranda Kerr Tea for One Teapot are presented in this paper. A computer-aided reverse engineering system (CARE System) was applied to minimize file errors generated by scanning Miranda Kerr Tea for One Teapot sample products made from Bone China clay. Digital data from the scanning process is used to design a teapot model that is precise and accurate. The digital data generated by Next Engine 3D and the priXa 1588 CMM is then converted into stereolithography (STL) file format (triangle-based data). The process of making 3D CAD models consists of: editing the 3D mesh from the scanning results, 3D CAD design forming the size of the fire, the size of the model, and the 3D CAD milling process using PowerSHAPE with the final result in the form of the surface of each part of the Teapot product. Manufacturing optimization to get the optimal machining strategy used PowerMILL and CNC machines. The casting process becomes a follow-up process after machining the mold of the designed product. This research has succeeded in demonstrating the advantages of using CARE System technology in the national ceramic industry in Indonesia so that it can compete at national and international levels. This is based on the magnitude of the RE error value of less than 1.00 mm with a total processing time of 43 hours 18 minutes 10 seconds and a total cost of about $ 4172.35.
- Published
- 2021
25. A Genetically Based Combination of Visual Saliency and Roughness for FR 3D Mesh Quality Assessment: A Statistical Study
- Author
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Anass Nouri, Christophe Charrier, Olivier Lezoray, Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen (GREYC), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), Equipe Monétique & Biométrie - Laboratoire GREYC - UMR6072, Lezoray, Olivier, Université Ibn Tofaïl (UIT), Equipe SAFE - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), and Normandie Université (NU)
- Subjects
General Computer Science ,Correlation coefficient ,Computer science ,02 engineering and technology ,Surface finish ,Spearman's rank correlation coefficient ,Rendering (computer graphics) ,visual saliency ,[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR] ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,0202 electrical engineering, electronic engineering, information engineering ,Polygon mesh ,patch ,ComputingMilieux_MISCELLANEOUS ,Visual saliency ,objective quality assessment ,graphs ,Ground truth ,business.industry ,020207 software engineering ,Pattern recognition ,visual attention ,[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV] ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,3D mesh ,Smoothing - Abstract
In this paper, we present a full-reference quality assessment metric based on the information of visual saliency. The saliency information is provided under the form of degrees associated to each vertex of the surface mesh. From these degrees, statistical attributes reflecting the structures of the reference and distorted meshes are computed. These are used by four comparisons functions genetically optimized that quantify the structure differences between a reference and a distorted mesh. We also present a statistical comparison study of six full-reference quality assessment metrics for 3D meshes. We compare the objective metrics results with humans subjective scores of quality considering the 3D meshes in one hand and the distorsion types in the other hand. Also, we show which metrics are statistically superior to their counterparts. For these comparisons we use the Spearman Rank Ordered Correlation Coefficient and the hypothetic test of Student (ttest). To attest the pertinence of the proposed approach, a comparison with a ground truth saliency and an application associated to the assessment of the visual rendering of smoothing algorithms are presented. Experimental results show that the proposed metric is very competitive with the state-of-the-art.
- Published
- 2020
26. A Geometry-aware compression of 3D mesh texture with random access
- Author
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Thomas Maugey, Aline Roumy, Frédéric Payan, Fatemeh Nasiri, Navid Mahmoudian Bidgoli, Analysis representation, compression and communication of visual data (Sirocco), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Projet MEDIACODING, Signal, Images et Systèmes (Laboratoire I3S - SIS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université Nice Sophia Antipolis (... - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS)
- Subjects
0303 health sciences ,Texture atlas ,Computer science ,business.industry ,030310 physiology ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,3d model ,030229 sport sciences ,texture map/atlas ,Random access ,Rendering (computer graphics) ,03 medical and health sciences ,0302 clinical medicine ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,Polygon mesh ,Computer vision ,Artificial intelligence ,business ,3D mesh ,Decoding methods ,ComputingMilieux_MISCELLANEOUS ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
A 3D mesh object is usually represented as a combination of several entities including geometrical information (i.e., the triangles and their position in space) and a texture atlas/map (i.e. a giant 2D image containing all the texture information that is mapped to the 3D object at the rendering stage). This atlas is usually compressed using a conventional 2D image coder, thus without taking into account the geometrical information. Moreover, the whole image is usually decoded even though only a subpart of the mesh is observed by a user. In this paper, we propose a novel approach to compress a texture atlas of a 3D model that enables random access during decoding, and nevertheless takes into account the correlation driven by the geometrical information. The experimental results demonstrate the benefits of the proposed coder.
- Published
- 2019
27. Analysis of digitized 3D mesh curvature histograms for reverse engineering
- Author
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William Puech, Roseline Bénière, Silvère Gauthier, Gérard Subsol, Custom CAD Software & Components (C4W), C4W, Image & Interaction (ICAR), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
- Subjects
Reverse engineering ,General Computer Science ,Computer science ,CAD ,02 engineering and technology ,Distribution ,Curvature ,computer.software_genre ,3D Mesh ,Robustness (computer science) ,Histogram ,0202 electrical engineering, electronic engineering, information engineering ,Polygon mesh ,Computer vision ,business.industry ,General Engineering ,020207 software engineering ,Digitized ,[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR] ,Fully automated ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,computer - Abstract
International audience; Today, it has become more frequent and reasonably easy to digitize the surface of 3D objects. However, the obtained results are often inaccurate and noisy. In this paper, we present an efficient method to analyze a curvature histogram from a digitized 3D surface using a real object. Moreover, we propose to use the curvature histogram analysis for many steps of a reverse engineering process, which can be used to retrieve a CAD model from a digitized one for example. Our objective is to design a fast and fully automated method, which is seldom seen in reverse engineering. Experimental results applied on digitized 3D meshes show the efficiency and the robustness of our proposed method.
- Published
- 2017
28. Just Noticeable Distortion Profile for Flat-Shaded 3D Mesh Surfaces
- Author
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Franck Hétroy-Wheeler, Florent Dupont, Kai Wang, Georges Nader, Geometry Processing and Constrained Optimization (M2DisCo), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), GIPSA - Architecture, Géométrie, Perception, Images, Gestes (GIPSA-AGPIG), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Capture and Analysis of Shapes in Motion (MORPHEO ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), ARC6 de la région Rhône-Alpes, Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Vertex (computer graphics) ,Computer science ,contrast sensitivity function ,02 engineering and technology ,Solid modeling ,Lossy compression ,[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG] ,psychophysical experiments ,human visual system ,Distortion ,0202 electrical engineering, electronic engineering, information engineering ,Polygon mesh ,Computer vision ,Just noticeable distortion ,Digital watermarking ,ComputingMethodologies_COMPUTERGRAPHICS ,business.industry ,020207 software engineering ,contrast masking ,Computer Graphics and Computer-Aided Design ,[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR] ,Visualization ,Vertex (geometry) ,Signal Processing ,Human visual system model ,020201 artificial intelligence & image processing ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,3D mesh ,Software - Abstract
International audience; It is common that a 3D mesh undergoes some lossy operations (e.g., compression, watermarking and transmission through noisy channels), which can introduce geometric distortions as a change in vertex position. In most cases the end users of 3D meshes are human beings; therefore, it is important to evaluate the visibility of introduced vertex displacement. In this paper we present a model for computing a Just Noticeable Distortion (JND) profile for flat-shaded 3D meshes. The proposed model is based on an experimental study of the properties of the human visual system while observing a flat-shaded 3D mesh surface, in particular the contrast sensitivity function and contrast masking. We first define appropriate local perceptual properties on 3D meshes. We then detail the results of a series of psychophysical experiments where we have measured the threshold needed for a human observer to detect the change in vertex position. These results allow us to compute the JND profile for flat-shaded 3D meshes. The proposed JND model has been evaluated via a subjective experiment, and applied to guide 3D mesh simplification as well as to determine the optimal vertex coordinates quantization level for a 3D model.
- Published
- 2016
29. Visual Contrast Sensitivity and Discrimination for 3D Meshes and their Applications
- Author
-
Franck Hétroy-Wheeler, Florent Dupont, Georges Nader, Kai Wang, Geometry Processing and Constrained Optimization (M2DisCo), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), GIPSA - Architecture, Géométrie, Perception, Images, Gestes (GIPSA-AGPIG), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Capture and Analysis of Shapes in Motion (MORPHEO ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), ARC6 de la Région Rhône-Alpes, Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Université Lumière - Lyon 2 (UL2)
- Subjects
Contrast Sensitivity Function ,Computer science ,media_common.quotation_subject ,Contrast Discrimination ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG] ,Psychophysical Experiments ,Geometric distortion ,3D Mesh ,Perception ,0202 electrical engineering, electronic engineering, information engineering ,Computer vision ,Polygon mesh ,Sensitivity (control systems) ,media_common ,ComputingMethodologies_COMPUTERGRAPHICS ,Series (mathematics) ,business.industry ,Geometric Distortion ,Human Visual System ,Visibility Threshold ,020207 software engineering ,Computer Graphics and Computer-Aided Design ,[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR] ,Task (computing) ,Human visual system model ,020201 artificial intelligence & image processing ,Artificial intelligence ,business - Abstract
International audience; In this paper, we first introduce an algorithm for estimating the visual contrast on a 3D mesh. We then perform a series of psychophysical experiments to study the effects of contrast sensitivity and contrast discrimination of the human visual system for the task of differentiating between two contrasts on a 3D mesh. The results of these experiments allow us to propose a perceptual model that is able to predict whether a change in local contrast on 3D mesh, induced by a local geometric distortion, is visible or not. Finally, we illustrate the utility of the proposed perceptual model in a number of applications: we compute the Just Noticeable Distortion (JND) profile for smooth-shaded 3D meshes and use the model to guide mesh processing algorithms.
- Published
- 2016
30. Full-reference saliency-based 3D mesh quality assessment index
- Author
-
Anass Nouri, Olivier Lezoray, Christophe Charrier, Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU), Equipe SAFE - Laboratoire GREYC - UMR6072, and IEEE
- Subjects
Quality assessment ,business.industry ,Computer science ,SIGNAL (programming language) ,020207 software engineering ,Pattern recognition ,02 engineering and technology ,graph ,Visualization ,Index (publishing) ,Salience (neuroscience) ,Metric (mathematics) ,0202 electrical engineering, electronic engineering, information engineering ,Graph (abstract data type) ,Objective quality assessment ,020201 artificial intelligence & image processing ,Polygon mesh ,Computer vision ,[INFO]Computer Science [cs] ,Artificial intelligence ,[MATH]Mathematics [math] ,business ,3D mesh ,Visual Saliency - Abstract
International audience; We propose in this paper a novel perceptual viewpoint-independent metric for the quality assessment of 3D meshes. This full-reference objective metric relies on the method proposed by Wang et al.[1] that compares the structural in-formations between an original signal and a distorted one. In order to extract the structural informations of a 3D mesh, we use a multi-scale visual saliency map on which we compute the local statistics. The experimental results attest the strong correlation between the objective scores provided by our metric and the human judgments. Also, comparisons with the state-of-the-art prove that our metric is very competitive.
- Published
- 2016
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