Proceedings Ninth IEEE International Conference on Computer Vision最新文献_第9页

"Perspective shape from shading" and viscosity solutions “透视形状从阴影”和粘度解决方案

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238433

E. Prados, O. Faugeras

引用次数: 140

Linear multiview reconstruction of points, lines, planes and cameras using a reference plane 线性多视图重建点，线，平面和相机使用参考平面

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238629

C. Rother

{"title":"Linear multiview reconstruction of points, lines, planes and cameras using a reference plane","authors":"C. Rother","doi":"10.1109/ICCV.2003.1238629","DOIUrl":"https://doi.org/10.1109/ICCV.2003.1238629","url":null,"abstract":"This paper presents a new linear method for reconstructing simultaneously 3D features (points, lines and planes) and cameras from many perspective views by solving a single linear system. It assumes that a real or virtual reference plane is visible in all views. We call it the Direct Reference Plane (DRP) method. It is well known that the projection relationship between uncalibrated cameras and 3D features is nonlinear in the absence of a reference plane. With a known reference plane, points and cameras have a linear relationship, as shown by Rother and Carlsson (2001). The main contribution of this paper is that lines and cameras, as well as, planes and cameras also have a linear relationship. Consequently, all 3D features and all cameras can be reconstructed simultaneously from a single linear system, which handles missing image measurements naturally. A further contribution is an extensive experimental comparison, using real data, of different reference plane and nonreference plane reconstruction methods. For difficult reference plane scenarios, with point or line features, the DRP method is superior to all compared methods. Finally, an extensive list of reference plane scenarios is presented, which shows the wide applicability of the DRP method.","PeriodicalId":131580,"journal":{"name":"Proceedings Ninth IEEE International Conference on Computer Vision","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683535","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: 36

Dominant sets and hierarchical clustering 优势集与层次聚类

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238367

M. Pavan, M. Pelillo

{"title":"Dominant sets and hierarchical clustering","authors":"M. Pavan, M. Pelillo","doi":"10.1109/ICCV.2003.1238367","DOIUrl":"https://doi.org/10.1109/ICCV.2003.1238367","url":null,"abstract":"Dominant sets are a new graph-theoretic concept that has proven to be relevant in partitional (flat) clustering as well as image segmentation problems. However, in many computer vision applications, such as the organization of an image database, it is important to provide the data to be clustered with a hierarchical organization, and it is not clear how to do this within the dominant set framework. We address precisely this problem, and present a simple and elegant solution to it. To this end, we consider a family of (continuous) quadratic programs, which contain a parameterized regularization term that controls the global shape of the energy landscape. When the regularization parameter is zero the local solutions are known to be in one-to-one correspondence with dominant sets, but when it is positive an interesting picture emerges. We determine bounds for the regularization parameter that allow us to exclude from the set of local solutions those inducing clusters of size smaller than a prescribed threshold. This suggests a new (divisive) hierarchical approach to clustering, which is based on the idea of properly varying the regularization parameter during the clustering process. Straightforward dynamics from evolutionary game theory are used to locate the solutions of the quadratic programs at each level of the hierarchy. We apply the proposed framework to the problem of organizing a shape database. Experiments with three different similarity matrices (and databases) reported in the literature have been conducted, and the results confirm the effectiveness of our approach.","PeriodicalId":131580,"journal":{"name":"Proceedings Ninth IEEE International Conference on Computer Vision","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129656569","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: 87

Combining gradient and albedo data for rotation invariant classification of 3D surface texture 结合梯度和反照率数据进行三维表面纹理旋转不变分类

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238437

Jiahua Wu, M. Chantler

引用次数: 27

Recognition with local features: the kernel recipe 局部特征识别:内核配方

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238351

C. Wallraven, B. Caputo, Arnulf B. A. Graf

引用次数: 426

Unsupervised non-parametric region segmentation using level sets 使用水平集的无监督非参数区域分割

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238636

T. Kadir, M. Brady

{"title":"Unsupervised non-parametric region segmentation using level sets","authors":"T. Kadir, M. Brady","doi":"10.1109/ICCV.2003.1238636","DOIUrl":"https://doi.org/10.1109/ICCV.2003.1238636","url":null,"abstract":"We present a novel non-parametric unsupervised segmentation algorithm based on region competition (Zhu and Yuille, 1996); but implemented within a level sets framework (Osher and Sethian, 1988). The key novelty of the algorithm is that it can solve N /spl ges/ 2 class segmentation problems using just one embedded surface; this is achieved by controlling the merging and splitting behaviour of the level sets according to a minimum description length (MDL) (Leclerc (1989) and Rissanen (1985)) cost function. This is in contrast to N class region-based level set segmentation methods to date which operate by evolving multiple coupled embedded surfaces in parallel (Chan et al., 2002). Furthermore, it operates in an unsupervised manner; it is necessary neither to specify the value of N nor the class models a-priori. We argue that the level sets methodology provides a more convenient framework for the implementation of the region competition algorithm, which is conventionally implemented using region membership arrays due to the lack of a intrinsic curve representation. Finally, we generalise the Gaussian region model used in standard region competition to the non-parametric case. The region boundary motion and merge equations become simple expressions containing cross-entropy and entropy terms.","PeriodicalId":131580,"journal":{"name":"Proceedings Ninth IEEE International Conference on Computer Vision","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124590306","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: 60

Filtering using a tree-based estimator 使用基于树的估计器进行过滤

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238467

B. Stenger, A. Thayananthan, P. Torr, R. Cipolla

引用次数: 167

A Bayesian network framework for relational shape matching 关系形状匹配的贝叶斯网络框架

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238412

Anand Rangarajan, J. Coughlan, A. Yuille

引用次数: 30

Improved fast gauss transform and efficient kernel density estimation 改进了快速高斯变换和高效核密度估计

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238383

Changjiang Yang, R. Duraiswami, N. Gumerov, L. Davis

引用次数: 516

A background layer model for object tracking through occlusion 一种通过遮挡进行目标跟踪的背景层模型

Proceedings Ninth IEEE International Conference on Computer Vision Pub Date : 2003-10-13 DOI: 10.1109/ICCV.2003.1238469

Yue Zhou, Hai Tao

引用次数: 109