Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)最新文献_第4页

Toward recovering shape and motion of 3D curves from multi-view image sequences 从多视图图像序列中恢复三维曲线的形状和运动

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786938

R. Carceroni, Kiriakos N. Kutulakos

引用次数: 9

Reconstruction of linearly parameterized models from single images with a camera of unknown focal length 用未知焦距的相机重建单幅图像的线性参数化模型

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784657

David Jelinek, C. J. Taylor

引用次数: 54

An efficient recursive factorization method for determining structure from motion 一种有效的从运动中确定结构的递归分解方法

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786930

Yanhua Li, M. Brooks

{"title":"An efficient recursive factorization method for determining structure from motion","authors":"Yanhua Li, M. Brooks","doi":"10.1109/CVPR.1999.786930","DOIUrl":"https://doi.org/10.1109/CVPR.1999.786930","url":null,"abstract":"A recursive method is presented for recovering 3D object shape and camera motion under orthography from an extended sequence of video images. This may be viewed as a natural extension of both the original and the sequential factorization methods. A critical aspect of these factorization approaches is the estimation of the so-called shape space, and they may in part be characterized by the manner in which this subspace is computed. If P points are tracked through F frames, the recursive least-squares method proposed in this paper updates the shape space with complexity O(P) per frame. In contrast, the sequential factorization method updates the shape space with complexity O(P/sup 2/) per frame. The original factorization method is intended to be used in batch mode using points tracked across all available frames. It effectively computes the shape space with complexity O(FP/sup 2/) after F frames. Unlike other methods, the recursive approach does not require the estimation or updating of a large measurement or covariance matrix. Experiments with real and synthetic image sequences confirm the recursive method's low computational complexity and good performance, and indicate that it is well suited to real-time applications.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":"7 1","pages":"138-143 Vol. 1"},"PeriodicalIF":0.0,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76021097","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

Advances in daylight statistical colour modelling 日光统计色彩建模的进展

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786957

D. Alexander

引用次数: 5

Surface reconstruction from multiple aerial images in dense urban areas 密集城区多幅航拍图像的地表重建

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784639

M. Fradkin, M. Roux, H. Maître, U. Leloglu

{"title":"Surface reconstruction from multiple aerial images in dense urban areas","authors":"M. Fradkin, M. Roux, H. Maître, U. Leloglu","doi":"10.1109/CVPR.1999.784639","DOIUrl":"https://doi.org/10.1109/CVPR.1999.784639","url":null,"abstract":"Accurate 3D surface models of dense urban areas are essential for a variety of applications, such as cartography, urban planning and monitoring mobile communications, etc. Since manual surface reconstruction is very costly and time-consuming, the development of automated algorithms is of great importance. While most of existing algorithms focus on surface reconstruction either in rural or sub-urban areas, we present an approach dealing with dense urban scenes. The approach utilizes different image-derived cues, like multiview stereo and color information, as well as the general scene knowledge, formulated in data-driven reasoning and geometric constraints. Another important feature of our approach is simultaneous processing of 2D and 3D data. Our approach begins with two independent tasks: stereo reconstruction using multiple views and region-based image segmentation, resulting in generation disparity and segmentation maps, respectively. Then, the information derived from the both maps is utilized for generation of a dense elevation map, through robust verification of planar surface approximations for the detected regions and imposition of geometric constraints. The approach has been successfully tested on complex residential and industrial scenes.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":"8 1-2","pages":"262-267 Vol. 2"},"PeriodicalIF":0.0,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91500286","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

A multiple hypothesis approach to figure tracking 图形跟踪的多假设方法

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784636

Tat-Jen Cham, James M. Rehg

引用次数: 400

Data-driven shape-from-shading using curvature consistency 使用曲率一致性的数据驱动的阴影形状

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786953

P. L. Worthington, E. Hancock

引用次数: 7

Color edge detection with the compass operator 颜色边缘检测与罗盘操作符

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784624

Mark A. Ruzon, Carlo Tomasi

引用次数: 197

Bias field estimation and adaptive segmentation of MRI data using a modified fuzzy C-means algorithm 基于改进模糊c均值算法的MRI数据偏置场估计与自适应分割

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786947

M. N. Ahmed, S. Yamany, A. Farag, T. Moriarty

引用次数: 73

Planar catadioptric stereo: geometry and calibration 平面反射立体:几何与标定

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786912

J. Gluckman, S. Nayar

引用次数: 116