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

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Precise sub-pixel estimation on area-based matching 基于区域匹配的精确亚像素估计
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937503
M. Shimizu, M. Okutomi
{"title":"Precise sub-pixel estimation on area-based matching","authors":"M. Shimizu, M. Okutomi","doi":"10.1109/ICCV.2001.937503","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937503","url":null,"abstract":"Area-based matching is a common procedure in various fields such as image-based measurements, stereo image processing, and fluidics. Sub-pixel estimation using parabola fitting over three points with their similarity measures is also a common method to increase the resolution of matching. However, few investigations or studies concerning the characteristics of this estimation have been reported. In this paper we have analyzed the sub-pixel estimation error by using an approximate image function and three kinds of similarity measures for matching. The results illustrate some inherently problematic phenomena such as so called \"pixel-locking\". In addition to this, we propose a new algorithm to greatly reduce sub-pixel estimation error. This method is independent from the similarity measure and quite simple to implement. The advantage of our novel method is confirmed through experiments using three different types of images.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"41 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":"116325424","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: 137
Calibration with robust use of cheirality by quasi-affine reconstruction of the set of camera projection centres 通过准仿射重建相机投影中心集，鲁棒地使用cheality进行校准
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937612
D. Nistér
{"title":"Calibration with robust use of cheirality by quasi-affine reconstruction of the set of camera projection centres","authors":"D. Nistér","doi":"10.1109/ICCV.2001.937612","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937612","url":null,"abstract":"A method for upgrading a projective reconstruction to metric is presented. The reconstruction is first transformed by considering cheirality so that the convex hull of the set of camera projection centres is the same as in the metric counterpart. The method then proceeds iteratively and starting from such a reconstruction is a necessary condition for many iterative calibration algorithms to converge. The results show that in practice it is also most often sufficient provided that the minimised objective function is a geometrically meaningful quantity. The method has been found extremely reliable for both large and small reconstructions in a large number of experiments on real data. When subjected to the common degeneracy of little or no rotation between the views, the method still yields a very reasonable member of the family of possible solutions. Furthermore, the method is very fast and therefore suitable for the purpose of viewing reconstructions.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"16 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":"127205474","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: 19
Topology free hidden Markov models: application to background modeling 无拓扑隐马尔可夫模型:在后台建模中的应用
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937532
B. Stenger, Visvanathan Ramesh, N. Paragios, Frans Coetzee, J. Buhmann
{"title":"Topology free hidden Markov models: application to background modeling","authors":"B. Stenger, Visvanathan Ramesh, N. Paragios, Frans Coetzee, J. Buhmann","doi":"10.1109/ICCV.2001.937532","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937532","url":null,"abstract":"Hidden Markov models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Their use involves an off-line learning step that is used as a basis for on-line decision making (i.e. a stationarity assumption on the model parameters). But, real-world applications are often non-stationary in nature. This leads to the need for a dynamic mechanism to learn and update the model topology as well as its parameters. This paper presents a new framework for HMM topology and parameter estimation in an online, dynamic fashion. The topology and parameter estimation is posed as a model selection problem with an MDL prior. Online modifications to the topology are made possible by incorporating a state splitting criterion. To demonstrate the potential of the algorithm, the background modeling problem is considered. Theoretical validation and real experiments are presented.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"55 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":"121452200","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: 245
A linear dual-space approach to 3D surface reconstruction from occluding contours using algebraic surfaces 利用代数曲面从遮挡轮廓重建三维表面的线性双空间方法
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937518
Kongbin Kang, Jean-Philippe Tarel, R. Fishman, D. Cooper
{"title":"A linear dual-space approach to 3D surface reconstruction from occluding contours using algebraic surfaces","authors":"Kongbin Kang, Jean-Philippe Tarel, R. Fishman, D. Cooper","doi":"10.1109/ICCV.2001.937518","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937518","url":null,"abstract":"We present a linear approach to the 3D reconstruction problem from occluding contours using algebraic surfaces. The problem of noise and missing data in the occluding contours extracted from the images leads us to this approach. Our approach is based first on the intensive use of the duality property between 3D points and tangent planes, and second on the algebraic representation of 3D surfaces by implicit polynomials of degree 2 and higher.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"10 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":"132398360","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: 33
BRDF/BTF measurement device BRDF/BTF测量装置
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937661
Kristin J. Dana
{"title":"BRDF/BTF measurement device","authors":"Kristin J. Dana","doi":"10.1109/ICCV.2001.937661","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937661","url":null,"abstract":"Capturing surface appearance is important for a large number of applications. Appearance of real world surfaces is difficult to model as it varies with the direction of illumination as well as the direction from which it is viewed. Consequently, measurements of the BRDF (bidirectional reflectance distribution function) have been important. In addition, many applications require measuring how the entire surface reflects light, i.e. spatially varying BRDF measurements are important as well. For compactness we refer to a spatially varying BRDF as a BTF (bidirectional texture function). Measurements of BRDF and/or BTF typically require significant resources in time and equipment. In this work, a device for BRDF/BTF measurement is presented that is compact, economical and convenient. The device uses the approach of curved mirrors to remove the need for hemispherical positioning of the camera and illumination source. Instead, simple planar translations of optical components are used to vary the illumination direction and to scan the surface. Furthermore, the measurement process is fast because the device enables simultaneous measurements of multiple viewing directions.","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":"130803168","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: 123
Optimal method for the affine F-matrix and its uncertainty estimation in the sense of both noise and outliers 仿射f矩阵的最优方法及其在噪声和离群值情况下的不确定性估计
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937620
Sami Sebastian Brandt, J. Heikkonen
{"title":"Optimal method for the affine F-matrix and its uncertainty estimation in the sense of both noise and outliers","authors":"Sami Sebastian Brandt, J. Heikkonen","doi":"10.1109/ICCV.2001.937620","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937620","url":null,"abstract":"We propose, in maximum likelihood sense, an optimal method for the affine fundamental matrix estimation in the presence of both Gaussian noise and outliers. It is based on weighting the squared residuals by the iteratively completed, residual posterior probabilities to be relevant. The proposed principle is also used for the covariance matrix estimation of the affine F-matrix where the novelty is in the fact that all data is used rather than the (erroneously) relevant classified matching points. The experiments on both synthetic and real data verify the optimality of the method in the sense of both false matches and Gaussian noise in data.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"35 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":"128363520","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: 14
Image segmentation with minimum mean cut 最小平均分割的图像分割
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937560
Song Wang, J. Siskind
{"title":"Image segmentation with minimum mean cut","authors":"Song Wang, J. Siskind","doi":"10.1109/ICCV.2001.937560","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937560","url":null,"abstract":"We introduce a new graph-theoretic approach to image segmentation based on minimizing a novel class of 'mean cut' cost functions. Minimizing these cost functions corresponds to finding a cut with minimum mean edge weight in a connected planar graph. This approach has several advantages over prior approaches to image segmentation. First, it allows cuts with both open and closed boundaries. Second, it guarantees that the partitions are connected. Third, the cost function does not introduce an explicit bias, such as a preference for large-area foregrounds, smooth or short boundaries, or similar-weight partitions. This lack of bias allows it to produce segmentations that are better aligned with image edges, even in the presence of long thin regions. Finally, the global minimum of this cost function is largely insensitive to the precise choice of edge-weight function. In particular, we show that the global minimum is invariant under a linear transformation of the edge weights and thus insensitive to image contrast. Building on algorithms by Ahuja et al. (1993), we present a polynomial-time algorithm for finding a global minimum of the mean-cut cost function and illustrate the results of applying that algorithm to several synthetic and real images.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"25 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":"131656951","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: 81
Harmonics extraction based on higher order statistics spectrum decomposition for a unified texture model 基于高阶统计谱分解的统一纹理模型谐波提取
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937631
Yong Huang, K. Chan, Zhong Huang
{"title":"Harmonics extraction based on higher order statistics spectrum decomposition for a unified texture model","authors":"Yong Huang, K. Chan, Zhong Huang","doi":"10.1109/ICCV.2001.937631","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937631","url":null,"abstract":"By considering a texture being composed of two orthogonal components in a unified texture model, the deterministic component and the indeterministic component, a method of harmonics extraction from a Higher Order Statistics (HOS) based spectral decomposition is developed. The method estimates the power spectrum based on the diagonal slice of the fourth-order cumulants From this spectrum, the harmonic frequencies can be easily extracted even for noisy images. The simulation and experimental results indicate that this method is effective for texture decomposition and performs better than the traditional lower order statistics based decomposition methods.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"19 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":"133979442","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: 4
On projection matrices P/sup k//spl rarr/P/sup 2/, k=3,...,6, and their applications in computer vision 在投影矩阵P/sup k//spl rarr/P/sup 2/上，k=3，…以及它们在计算机视觉中的应用
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937547
L. Wolf, A. Shashua
{"title":"On projection matrices P/sup k//spl rarr/P/sup 2/, k=3,...,6, and their applications in computer vision","authors":"L. Wolf, A. Shashua","doi":"10.1109/ICCV.2001.937547","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937547","url":null,"abstract":"Projection matrices from projective spaces P/sup 3/ to P/sup 2/ have long been used in multiple-view geometry to model the perspective projection created by the pin-hole camera. In this work we introduce higher-dimensional mappings P/sup k//spl rarr/P/sup 2/, k=4,5,6 for the representation of various applications in which the world we view is no longer rigid. We also describe the multi-view constraints from these new projection matrices and methods for extracting the (non-rigid) structure and motion for each application.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"23 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":"116821452","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: 15
Pairwise face recognition 两两人脸识别
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 Pub Date : 2001-07-07 DOI: 10.1109/ICCV.2001.937637
G. Guo, HongJiang Zhang, S. Li
{"title":"Pairwise face recognition","authors":"G. Guo, HongJiang Zhang, S. Li","doi":"10.1109/ICCV.2001.937637","DOIUrl":"https://doi.org/10.1109/ICCV.2001.937637","url":null,"abstract":"We develop a pairwise classification framework for face recognition, in which a C class face recognition problem is divided into a set of C(C-1)/2 two class problems. Such a problem decomposition not only leads to a set of simpler classification problems to be solved, thereby increasing overall classification accuracy, but also provides a framework for independent feature selection for each pair of classes. A simple feature ranking strategy is used to select a small subset of the features for each pair of classes. Furthermore, we evaluate two classification methods under the pairwise comparison framework: the Bayes classifier and the AdaBoost. Experiments on a large face database with 1079 face images of 137 individuals indicate that 20 features are enough to achieve a relatively high recognition accuracy, which demonstrates the effectiveness of the pairwise recognition framework.","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":"126876517","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: 46
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