2009 IEEE Conference on Computer Vision and Pattern Recognition最新文献_第5页

Disambiguating the recognition of 3D objects 消除三维物体识别的歧义

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206683

Gutemberg Guerra-Filho

引用次数: 4

Towards high-resolution large-scale multi-view stereo 迈向高分辨率大尺度多视点立体

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206617

Hoang-Hiep Vu, R. Keriven, Patrick Labatut, Jean-Philippe Pons

引用次数: 279

Learning rotational features for filament detection 学习旋转特征的灯丝检测

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206511

Germán González, F. Fleuret, P. Fua

引用次数: 42

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206783

José A. Rodríguez-Serrano, F. Perronnin, J. Lladós, Gemma Sánchez

{"title":"A similarity measure between vector sequences with application to handwritten word image retrieval","authors":"José A. Rodríguez-Serrano, F. Perronnin, J. Lladós, Gemma Sánchez","doi":"10.1109/CVPR.2009.5206783","DOIUrl":"https://doi.org/10.1109/CVPR.2009.5206783","url":null,"abstract":"This article proposes a novel similarity measure between vector sequences. Recently, a model-based approach was introduced to address this issue. It consists in modeling each sequence with a continuous Hidden Markov Model (CHMM) and computing a probabilistic measure of similarity between C-HMMs. In this paper we propose to model sequences with semi-continuous HMMs (SC-HMMs): the Gaussians of the SC-HMMs are constrained to belong to a shared pool of Gaussians. This constraint provides two major benefits. First, the a priori information contained in the common set of Gaussians leads to a more accurate estimate of the HMM parameters. Second, the computation of a probabilistic similarity between two SC-HMMs can be simplified to a Dynamic Time Warping (DTW) between their mixture weight vectors, which reduces significantly the computational cost. Experimental results on a handwritten word retrieval task show that the proposed similarity outperforms the traditional DTW between the original sequences, and the model-based approach which uses C-HMMs. We also show that this increase in accuracy can be traded against a significant reduction of the computational cost (up to 100 times).","PeriodicalId":386532,"journal":{"name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114413139","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: 35

Coded exposure deblurring: Optimized codes for PSF estimation and invertibility 编码曝光去模糊:PSF估计和可逆性的优化代码

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206685

Amit K. Agrawal, Yi Xu

{"title":"Coded exposure deblurring: Optimized codes for PSF estimation and invertibility","authors":"Amit K. Agrawal, Yi Xu","doi":"10.1109/CVPR.2009.5206685","DOIUrl":"https://doi.org/10.1109/CVPR.2009.5206685","url":null,"abstract":"We consider the problem of single image object motion deblurring from a static camera. It is well-known that deblurring of moving objects using a traditional camera is ill-posed, due to the loss of high spatial frequencies in the captured blurred image. A coded exposure camera modulates the integration pattern of light by opening and closing the shutter within the exposure time using a binary code. The code is chosen to make the resulting point spread function (PSF) invertible, for best deconvolution performance. However, for a successful deconvolution algorithm, PSF estimation is as important as PSF invertibility. We show that PSF estimation is easier if the resulting motion blur is smooth and the optimal code for PSF invertibility could worsen PSF estimation, since it leads to non-smooth blur. We show that both criterions of PSF invertibility and PSF estimation can be simultaneously met, albeit with a slight increase in the deconvolution noise. We propose design rules for a code to have good PSF estimation capability and outline two search criteria for finding the optimal code for a given length. We present theoretical analysis comparing the performance of the proposed code with the code optimized solely for PSF invertibility. We also show how to easily implement coded exposure on a consumer grade machine vision camera with no additional hardware. Real experimental results demonstrate the effectiveness of the proposed codes for motion deblurring.","PeriodicalId":386532,"journal":{"name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123445806","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: 89

Motion pattern interpretation and detection for tracking moving vehicles in airborne video 机载视频中运动车辆跟踪的运动模式解释与检测

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206541

Qian Yu, G. Medioni

{"title":"Motion pattern interpretation and detection for tracking moving vehicles in airborne video","authors":"Qian Yu, G. Medioni","doi":"10.1109/CVPR.2009.5206541","DOIUrl":"https://doi.org/10.1109/CVPR.2009.5206541","url":null,"abstract":"Detection and tracking of moving vehicles in airborne videos is a challenging problem. Many approaches have been proposed to improve motion segmentation on frame-by-frame and pixel-by-pixel bases, however, little attention has been paid to analyze the long-term motion pattern, which is a distinctive property for moving vehicles in airborne videos. In this paper, we provide a straightforward geometric interpretation of a general motion pattern in 4D space (x, y, vx, vy). We propose to use the tensor voting computational framework to detect and segment such motion patterns in 4D space. Specifically, in airborne videos, we analyze the essential difference in motion patterns caused by parallax and independent moving objects, which leads to a practical method for segmenting motion patterns (flows) created by moving vehicles in stabilized airborne videos. The flows are used in turn to facilitate detection and tracking of each individual object in the flow. Conceptually, this approach is similar to “track-before-detect” techniques, which involves temporal information in the process as early as possible. As shown in the experiments, many difficult cases in airborne videos, such as parallax, noisy background modeling and long term occlusions, can be addressed by our approach.","PeriodicalId":386532,"journal":{"name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116810879","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: 58

Fast multiple shape correspondence by pre-organizing shape instances 通过预先组织形状实例，快速实现多个形状对应

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/cvpr.2009.5206611

B. Munsell, Andrew Temlyakov, Song Wang

引用次数: 21

Towards a practical face recognition system: Robust registration and illumination by sparse representation 一个实用的人脸识别系统:稀疏表示的鲁棒配准和照明

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206654

Andrew Wagner, John Wright, Arvind Ganesh, Zihan Zhou, Yi Ma

{"title":"Towards a practical face recognition system: Robust registration and illumination by sparse representation","authors":"Andrew Wagner, John Wright, Arvind Ganesh, Zihan Zhou, Yi Ma","doi":"10.1109/CVPR.2009.5206654","DOIUrl":"https://doi.org/10.1109/CVPR.2009.5206654","url":null,"abstract":"Most contemporary face recognition algorithms work well under laboratory conditions but degrade when tested in less-controlled environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, alignment, pose, and occlusion. In this paper, we propose a simple and practical face recognition system that achieves a high degree of robustness and stability to all these variations. We demonstrate how to use tools from sparse representation to align a test face image with a set of frontal training images in the presence of significant registration error and occlusion. We thoroughly characterize the region of attraction for our alignment algorithm on public face datasets such as Multi-PIE. We further study how to obtain a sufficient set of training illuminations for linearly interpolating practical lighting conditions. We have implemented a complete face recognition system, including a projector-based training acquisition system, in order to evaluate how our algorithms work under practical testing conditions. We show that our system can efficiently and effectively recognize faces under a variety of realistic conditions, using only frontal images under the proposed illuminations as training.","PeriodicalId":386532,"journal":{"name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123988885","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: 211

A nonparametric Riemannian framework for processing high angular resolution diffusion images (HARDI) 处理高角分辨率扩散图像的非参数黎曼框架

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206843

A. Goh, C. Lenglet, P. Thompson, R. Vidal

引用次数: 36

Efficient planar graph cuts with applications in Computer Vision 高效平面图形切割及其在计算机视觉中的应用

2009 IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 2009-06-20 DOI: 10.1109/CVPR.2009.5206863

Frank R. Schmidt, Eno Töppe, D. Cremers

引用次数: 83