2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission最新文献_第5页

A Multi-camera, Multi-projector Super-Resolution Framework for Structured Light 一种用于结构光的多相机、多投影仪超分辨率框架

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.57

Michael Weinmann, Christopher Schwartz, R. Ruiters, R. Klein

引用次数: 37

A Feature-Preserved Canonical Form for Non-rigid 3D Meshes 非刚性三维网格的特征保留规范形式

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.22

Z. Lian, A. Godil

{"title":"A Feature-Preserved Canonical Form for Non-rigid 3D Meshes","authors":"Z. Lian, A. Godil","doi":"10.1109/3DIMPVT.2011.22","DOIUrl":"https://doi.org/10.1109/3DIMPVT.2011.22","url":null,"abstract":"Measuring the dissimilarity between non-rigid objects is a challenging problem in 3D shape retrieval. One potential solution is to construct the models' 3D canonical forms (i.e., isometry-invariant representations in 3D Euclidean space) on which any rigid shape matching algorithm can be applied. However, existing methods, which are typically based on embedding procedures, result in greatly distorted canonical forms, and thus could not provide satisfactory performance to distinguish non-rigid models. In this paper, we present a feature-preserved canonical form for non-rigid 3D meshes. The basic idea is to naturally deform original models against corresponding initial canonical forms calculated by Multidimensional Scaling (MDS). Specifically, objects are first segmented into near-rigid subparts, and then, through properly-designed rotations and translations, original subparts are transformed into poses that correspond well with their positions and directions on MDS canonical forms. Final results are obtained by solving some nonlinear minimization problems for optimal alignments and smoothing boundaries between subparts. Experiments on a widely utilized non-rigid 3D shape benchmark not only verify the advantages of our algorithm against existing approaches, but also demonstrate that, with the help of the proposed canonical form, we can obtain significantly better retrieval accuracy compared to the state-of-the-art.","PeriodicalId":330003,"journal":{"name":"2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129496015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Scene Cut: Class-Specific Object Detection and Segmentation in 3D Scenes 场景切割:3D场景中特定类别的对象检测和分割

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.30

Jan Knopp, Mukta Prasad, L. Gool

引用次数: 26

Cutting-Plane Training of Non-associative Markov Network for 3D Point Cloud Segmentation 三维点云分割的非关联马尔可夫网络切面训练

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.10

Roman Shapovalov, A. Velizhev

引用次数: 46

Fast Stereo Matching of Feature Links 特征链接的快速立体匹配

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.41

Chang-Il Kim, Soon-Yong Park

引用次数: 15

Automatic Keypoint Detection on 3D Faces Using a Dictionary of Local Shapes 使用局部形状字典的3D人脸关键点自动检测

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.33

Clement Creusot, Nick E. Pears, J. Austin

{"title":"Automatic Keypoint Detection on 3D Faces Using a Dictionary of Local Shapes","authors":"Clement Creusot, Nick E. Pears, J. Austin","doi":"10.1109/3DIMPVT.2011.33","DOIUrl":"https://doi.org/10.1109/3DIMPVT.2011.33","url":null,"abstract":"Keypoints on 3D surfaces are points that can be extracted repeatably over a wide range of 3D imaging conditions. They are used in many 3D shape processing applications, for example, to establish a set of initial correspondences across a pair of surfaces to be matched. Typically, keypoints are extracted using extremal values of a function over the 3D surface, such as the descriptor map for Gaussian curvature. That approach works well for salient points, such as the nose-tip, but can not be used with other less pronounced local shapes. In this paper, we present an automatic method to detect keypoints on 3D faces, where these keypoints are locally similar to a set of previously learnt shapes, constituting a 'local shape dictionary'. The local shapes are learnt at a set of 14 manually-placed landmark positions on the human face. Local shapes are characterised by a set of 10 shape descriptors computed over a range of scales. For each landmark, the proportion of face meshes that have an associated keypoint detection is used as a performance indicator. Repeatability of the extracted keypoints is measured across the FRGC v2 database.","PeriodicalId":330003,"journal":{"name":"2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134085104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

Visual Hull from Imprecise Polyhedral Scene 视觉船体从不精确多面体场景

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.28

Peng He, A. Edalat

引用次数: 1

Toward Automatic 3D Generic Object Modeling from One Single Image 从单幅图像实现自动3D通用对象建模

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.11

Min Sun, S. Kumar, G. Bradski, S. Savarese

引用次数: 8

Sampling Relevant Points for Surface Registration 为表面配准采样相关点

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.43

A. Torsello, E. Rodolà, A. Albarelli

{"title":"Sampling Relevant Points for Surface Registration","authors":"A. Torsello, E. Rodolà, A. Albarelli","doi":"10.1109/3DIMPVT.2011.43","DOIUrl":"https://doi.org/10.1109/3DIMPVT.2011.43","url":null,"abstract":"Surface registration is a fundamental step in the reconstruction of three-dimensional objects. This is typically a two-step process where an initial coarse motion estimation is followed by a refinement step that almost invariably is some variant of Iterative Closest Point (ICP), which iteratively minimizes a distance function measured between pairs of selected neighboring points. The selection of relevant points on one surface to match against points on the other surface is an important issue in any efficient implementation of ICP, with strong implications both on the convergence speed and on the quality of the final alignment. This is due to the fact that typically on a surface there are a lot of low-curvature points that scarcely constrain the rigid transformation and an order of magnitude less descriptive points that are more relevant for finding the correct alignment. This results in a tendency of surfaces to \"over fit'' noise on low-curvature areas sliding away from the correct alignment. In this paper we propose a novel relevant-point sampling approach for ICP based on the idea that points in an area of great change constrain the transformation more and thus should be sampled with higher frequency. Experimental evaluations confront the alignment accuracy obtained with the proposed approach with those obtained with the commonly adopted uniform sub sampling and normal-space sampling strategies.","PeriodicalId":330003,"journal":{"name":"2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133289283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Electric Appliance Parts Classification Using a Measure Combining the Whole Shape and Local Shape Distribution Similarities 整体形状与局部形状分布相似度相结合的电器零件分类方法

2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission Pub Date : 2011-05-16 DOI: 10.1109/3DIMPVT.2011.44

Ryo Hanai, Kimitoshi Yamazaki, Hiroaki Yaguchi, K. Okada, M. Inaba

引用次数: 2