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Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001最新文献

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3D object recognition using shape similiarity-based aspect graph 基于形状相似度的三维物体识别
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937526
C. Cyr, B. Kimia
{"title":"3D object recognition using shape similiarity-based aspect graph","authors":"C. Cyr, B. Kimia","doi":"10.1109/ICCV.2001.937526","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937526","url":null,"abstract":"We present an aspect-graph approach to 3D object recognition where the definition of an aspect is motivated by its role in the subsequent recognition step. Specifically, we measure the similarity between two views by a 2D shape metric of similarity measuring the distance between the projected segmented shapes of the 3D object. This endows the viewing sphere with a metric which is used to group similar views into aspects, and to represent each aspect by a prototype. The same shape similarity metric is then used to rate the similarity between unknown views of unknown objects and stored prototypes to identify the object and its pose. The performance of this approach on a database of 18 objects each viewed in five degree increments along the ground viewing plane is demonstrated.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123311925","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: 247
A general imaging model and a method for finding its parameters 一种通用成像模型及其参数的求取方法
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937611
M. Grossberg, S. Nayar
{"title":"A general imaging model and a method for finding its parameters","authors":"M. Grossberg, S. Nayar","doi":"10.1109/ICCV.2001.937611","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937611","url":null,"abstract":"Linear perspective projection has served as the dominant imaging model in computer vision. Recent developments in image sensing make the perspective model highly restrictive. This paper presents a general imaging model that can be used to represent an arbitrary imaging system. It is observed that all imaging systems perform a mapping from incoming scene rays to photo-sensitive elements on the image detector. This mapping can be conveniently described using a set of virtual sensing elements called raxels. Raxels include geometric, radiometric and optical properties. We present a novel calibration method that uses structured light patterns to extract the raxel parameters of an arbitrary imaging system. Experimental results for perspective as well as ion-perspective imaging systems are included.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124742217","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: 298
Face recognition with support vector machines: global versus component-based approach 基于支持向量机的人脸识别:全局与基于组件的方法
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937693
B. Heisele, Purdy Ho, T. Poggio
{"title":"Face recognition with support vector machines: global versus component-based approach","authors":"B. Heisele, Purdy Ho, T. Poggio","doi":"10.1109/ICCV.2001.937693","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937693","url":null,"abstract":"We present a component-based method and two global methods for face recognition and evaluate them with respect to robustness against pose changes. In the component system we first locate facial components, extract them and combine them into a single feature vector which is classified by a Support Vector Machine (SVM). The two global systems recognize faces by classifying a single feature vector consisting of the gray values of the whole face image. In the first global system we trained a single SVM classifier for each person in the database. The second system consists of sets of viewpoint-specific SVM classifiers and involves clustering during training. We performed extensive tests on a database which included faces rotated up to about 40/spl deg/ in depth. The component system clearly outperformed both global systems on all tests.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124149092","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: 548
Efficient dense depth estimation from dense multiperspective panoramas 从密集的多视角全景图高效密集深度估计
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937507
Yin Li, Chi-Keung Tang, H. Shum
{"title":"Efficient dense depth estimation from dense multiperspective panoramas","authors":"Yin Li, Chi-Keung Tang, H. Shum","doi":"10.1109/ICCV.2001.937507","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937507","url":null,"abstract":"In this paper we study how to compute a dense depth map with panoramic field of view (e.g., 360 degrees) from multi-perspective panoramas. A dense sequence of multiperspective panoramas is used for better accuracy and reduced ambiguity by taking advantage of significant data redundancy. To speed up the reconstruction, we derive an approximate epipolar plane image that is associated with the planar sweeping camera setup, and use one-dimensional window for efficient matching. To address the aperture problem introduced by one-dimensional window matching, we keep a set of possible depth candidates from matching scores. These candidates are then passed to a novel two-pass tensor voting scheme to select the optimal depth. By propagating the continuity and uniqueness constraints non-iteratively in the voting process, our method produces high-quality reconstruction results even when significant occlusion is present. Experiments on challenging synthetic and real scenes demonstrate the effectiveness and efficacy of our method.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125544700","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: 30
Articulated soft objects for video-based body modeling 基于视频的人体建模的铰接软物体
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937545
Ralf Plänkers, P. Fua
{"title":"Articulated soft objects for video-based body modeling","authors":"Ralf Plänkers, P. Fua","doi":"10.1109/ICCV.2001.937545","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937545","url":null,"abstract":"We develop a framework for 3-D shape and motion recovery of articulated deformable objects. We propose a formalism that incorporates the use of implicit surfaces into earlier robotics approaches that were designed to handle articulated structures. We demonstrate its effectiveness for human body modeling from video sequences. Our method is both robust and generic. It could easily be applied to other shape and motion recovery problems.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125544705","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: 159
Video georegistration: algorithm and quantitative evaluation 视频地理配准:算法与定量评价
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937646
Richard P. Wildes, D. Hirvonen, S. Hsu, Rakesh Kumar, W. Lehman, B. Matei, Wenyi Zhao
{"title":"Video georegistration: algorithm and quantitative evaluation","authors":"Richard P. Wildes, D. Hirvonen, S. Hsu, Rakesh Kumar, W. Lehman, B. Matei, Wenyi Zhao","doi":"10.1109/ICCV.2001.937646","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937646","url":null,"abstract":"An algorithm is presented for video georegistration, with a particular concern for aerial video, i.e., video captured from an airborne platform. The algorithm's input is a video stream with telemetry (camera model specification sufficient to define an initial estimate of the view) and geodetically calibrated reference imagery (coaligned digital orthoimage and elevation map). The output is a spatial registration of the video to the reference so that it inherits the available geodetic coordinates. The video is processed in a continuous fashion to yield a corresponding stream of georegistered results. Quantitative results of evaluating the developed approach with real world aerial video also are presented. The results suggest that the developed approach may provide valuable input to the analysis and interpretation of aerial video.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"3 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129977912","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: 69
A global matching framework for stereo computation 立体计算的全局匹配框架
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937562
Hai Tao, H. Sawhney, Rakesh Kumar
{"title":"A global matching framework for stereo computation","authors":"Hai Tao, H. Sawhney, Rakesh Kumar","doi":"10.1109/ICCV.2001.937562","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937562","url":null,"abstract":"This paper presents a new global matching framework for stereo computation. In this framework, the second view is first predicted from the reference view using the depth information. A global match measure is then defined as the similarity function between the predicted image and the actual image. Stereo computation is converted into a search problem where the goal is to find the depth map that maximizes the global match measure. The major advantage of this framework is that the global visibility constraint is inherently enforced in the computation. This paper explores several key components of this framework including (1) three color segmentation based depth representations, (2) an incremental warping algorithm that dramatically reduces the computational complexity, and (3) scene constraints such as the smoothness constraint and the color similarity constraint. Experimental results using different types of depth representations are presented. The quality of the computed depth maps is demonstrated through image-based rendering from new viewpoints.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130082866","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: 306
Statistical calibration of CCD imaging process CCD成像过程的统计校准
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937555
Yanghai Tsin, Visvanathan Ramesh, T. Kanade
{"title":"Statistical calibration of CCD imaging process","authors":"Yanghai Tsin, Visvanathan Ramesh, T. Kanade","doi":"10.1109/ICCV.2001.937555","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937555","url":null,"abstract":"Charge-Coupled Device (CCD) cameras are widely used imaging sensors in computer vision systems. Many photometric algorithms, such as shape from shading, color constancy and photometric stereo, implicitly assume that the image intensity is proportional to scene radiance. The actual image measurements deviate significantly from this assumption since the transformation from scene radiance to image intensity is non-linear and is a function of various factors including: noise sources in the CCD sensor, as well as various transformations occurring in the camera including: white balancing, gamma correction and automatic gain control. This paper illustrates how careful modeling of the error sources and the various processing steps enable us to accurately estimate the \"response function\", the inverse mapping from image measurements to scene radiance for a given camera exposure setting. It is shown that the estimation algorithm outperforms the calibration procedures known to us in terms of reduced bias and variance. Further, we demonstrate how the error modelling helps us to obtain uncertainty estimates of the camera irradiance value. The power of this uncertainty modeling is illustrated by a vision task involving High Dynamic Range image generation followed by change detection. Change can be detected reliably even in situation where the two images (the reference scene image and the current image) are taken several hours apart.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129209697","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: 264
Cheirality in epipolar geometry 极极几何中的正义性
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937564
Tomáš Werner, T. Pajdla
{"title":"Cheirality in epipolar geometry","authors":"Tomáš Werner, T. Pajdla","doi":"10.1109/ICCV.2001.937564","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937564","url":null,"abstract":"The image points in two images satisfy epipolar constraint. However, not all sets of points satisfying epipolar constraint correspond to any real geometry because there can exist no cameras and scene points projecting to given image points such that all image points have positive depth. Using the cheirability theory due to Hartley and previous work an oriented projective geometry, we give necessary and sufficient conditions for an image point set to correspond to any real geometry. For images from conventional cameras, this condition is simple and given in terms of epipolar lines and epipoles. Surprising, this is not sufficient for central panoramic cameras. Apart from giving the insight to epipolar geometry, among the applications are reducing the search space and ruling out impossible matches in stereo, and ruling out impossible solutions for a fundamental matrix computed from seven points.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116393773","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: 29
Concentric mosaic(s), planar motion and 1D cameras 同心圆马赛克，平面运动和1D相机
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937624
Long Quan, Le Lu, H. Shum, M. Lhuillier
{"title":"Concentric mosaic(s), planar motion and 1D cameras","authors":"Long Quan, Le Lu, H. Shum, M. Lhuillier","doi":"10.1109/ICCV.2001.937624","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937624","url":null,"abstract":"General SFM methods give poor results for images captured by constrained motions such as planar motion of concentric mosaics (CM). In this paper we propose new SFM algorithms for both images captured by CM and composite mosaic images from CM. We first introduce ID affine camera model for completing 1D camera models. Then we show that a 2D image captured by CM can be decoupled into two 1D images: one 1D projective and one ID affine; a composite mosaic image can by rebinned into a calibrated ID panorama projective camera. Finally we describe subspace reconstruction methods and demonstrate both in theory and experiments the advantage of the decomposition method over the general SFM methods by incorporating the constrained motion into the earliest stage of motion analysis.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"341 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116477937","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: 3
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