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

Constrained self-calibration 受约束的自校准

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784974

J. Mendelsohn, Kostas Daniilidis

引用次数: 11

Indexing using a spectral encoding of topological structure 索引使用频谱编码的拓扑结构

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784726

A. Shokoufandeh, Sven J. Dickinson, Kaleem Siddiqi, S. Zucker

引用次数: 177

Interpolating view and scene motion by dynamic view morphing 通过动态视图变形插值视图和场景运动

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.786968

R. A. Manning, C. Dyer

引用次数: 83

Efficient bundle adjustment with virtual key frames: a hierarchical approach to multi-frame structure from motion 基于虚拟关键帧的有效束调整:一种从运动到多帧结构的分层方法

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784733

H. Shum, Zhengyou Zhang, Qifa Ke

引用次数: 81

Robot localization using uncalibrated camera invariants 利用未标定的相机不变量进行机器人定位

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784658

M. Werman, M. Qiu, Subhashis Banerjee, Sumantra Dutta Roy

引用次数: 26

Robust and efficient image alignment with spatially varying illumination models 鲁棒和有效的图像对齐与空间变化的照明模型

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784625

S. Lai, M. Fang

引用次数: 45

Sensor planning for a trinocular active vision system 三眼主动视觉系统的传感器规划

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784649

Peter Lehel, E. Hemayed, A. Farag

引用次数: 16

Extending superquadrics with exponent functions: modeling and reconstruction 用指数函数扩展超二次曲面:建模与重构

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784611

Lin Zhou, C. Kambhamettu

{"title":"Extending superquadrics with exponent functions: modeling and reconstruction","authors":"Lin Zhou, C. Kambhamettu","doi":"10.1109/CVPR.1999.784611","DOIUrl":"https://doi.org/10.1109/CVPR.1999.784611","url":null,"abstract":"Superquadrics are a family of parametric shapes which can model a diverse set of objects. They have received significant attention because of their compact representation and robust methods for recovery of 3D models. However, their assumption of intrinsical symmetry fails in modeling numerous real-world examples such as human, body, animals, and other naturally occurring objects. In this paper, we present a novel approach, which is called extended superquadric to extend superquadric's representation power with exponent functions. An extended superquadric model can be deformed in any direction because it extends the exponents of superquadrics from constants to functions of the latitude and longitude angles in the spherical coordinate system. Thus extended superquadrics can model more complex shapes than superquadrics. It also maintains many desired properties of superquadrics such as compactness controllability, and intuitive meaning, which are all advantageous for shape modeling, recognition, and reconstruction. In this paper, besides the use of extended superquadrics for modeling, we also discuss our research into the recovery of extended superquadrics from 3D information (reconstruction). Experimental results of fitting extended superquadrics to 3D real data are presented. Our results are very encouraging and indicate that the use of extended superquadric is a promising paradigm for shape representation and recovery in computers vision and has potential benefits for the generation of synthetic images for computer graphics.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81213883","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: 52

A dependency-based framework of combining multiple experts for the recognition of unconstrained handwritten numerals 结合多个专家的基于依赖的框架，用于无约束手写数字的识别

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784619

H. Kang, Seong-Whan Lee

{"title":"A dependency-based framework of combining multiple experts for the recognition of unconstrained handwritten numerals","authors":"H. Kang, Seong-Whan Lee","doi":"10.1109/CVPR.1999.784619","DOIUrl":"https://doi.org/10.1109/CVPR.1999.784619","url":null,"abstract":"Although Behavior-Knowledge Space (BKS) method does not need any assumptions in combining multiple experts, it should build theoretically exponential storage spaces for storing and managing jointly observed K decisions from K experts. That is, combining K experts needs a (K+1)st-order probability distribution. However, it is well known that the distribution becomes unmanageable in storing and estimating, even for a small K. In order to overcome such weakness, it would be attractive to decompose the distribution into a number of component distributions and to approximate the distribution with a product of the component distributions. One of such previous works is to apply a conditional independence assumption to the distribution. Another work is to approximate the distribution with a product of only first-order tree dependencies or second-order distributions. In this paper, a dependency-based framework is proposed to optimality approximate a probability distribution with a product set of dth-order dependencies where 1<d<K, and to combine multiple experts based on the product set using the Bayesian formalism. This framework was experimented and evaluated with a standardized CEN-PARIMl data base.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82250588","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: 9

Torque-based recursive filtering approach to the recovery of 3D articulated motion from image sequences 基于转矩的递归滤波方法从图像序列中恢复三维关节运动

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI: 10.1109/CVPR.1999.784656

Hiroyuki Segawa, T. Totsuka

引用次数: 9