2003 Conference on Computer Vision and Pattern Recognition Workshop最新文献

Automated Posture Analysis for Detecting Learner's Interest Level 用于检测学习者兴趣水平的自动姿势分析

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10047

Selene Mota, Rosalind W. Picard

引用次数: 351

Robust LDA Classification by Subsampling 基于子抽样的鲁棒LDA分类

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10089

S. Fidler, A. Leonardis

引用次数: 26

Enforcing Constraints for Human Body Tracking 强制约束人体跟踪

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10101

D. Demirdjian

引用次数: 32

A Statistical Assessment of Subject Factors in the PCA Recognition of Human Faces 人脸主成分分析中主体因素的统计分析

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10088

G. Givens, Ross Beveridge, B. Draper, D. Bolme

{"title":"A Statistical Assessment of Subject Factors in the PCA Recognition of Human Faces","authors":"G. Givens, Ross Beveridge, B. Draper, D. Bolme","doi":"10.1109/CVPRW.2003.10088","DOIUrl":"https://doi.org/10.1109/CVPRW.2003.10088","url":null,"abstract":"Some people's faces are easier to recognize than others, but it is not obvious what subject-specific factors make individual faces easy or difficult to recognize. This study considers 11 factors that might make recognition easy or difficult for 1,072 human subjects in the FERET dataset. The specific factors are: race (white, Asian, African-American, or other), gender, age (young or old), glasses (present or absent), facial hair (present or absent), bangs (present or absent), mouth (closed or other), eyes (open or other), complexion (clear or other), makeup (present or absent), and expression (neutral or other). An ANOVA is used to determine the relationship between these subject covariates and the distance between pairs of images of the same subject in a standard Eigenfaces subspace. Some results are not terribly surprising. For example, the distance between pairs of images of the same subject increases for people who change their appearance, e.g., open and close their eyes, open and close their mouth or change expression. Thus changing appearance makes recognition harder. Other findings are surprising. Distance between pairs of images for subjects decreases for people who consistently wear glasses, so wearing glasses makes subjects more recognizable. Pairwise distance also decreases for people who are either Asian or African-American rather than white. A possible shortcoming of our analysis is that minority classifications such as African-Americans and wearers-of-glasses are underrepresented in training. Followup experiments with balanced training addresses this concern and corroborates the original findings. Another possible shortcoming of this analysis is the novel use of pairwise distance between images of a single person as the predictor of recognition difficulty. A separate experiment confirms that larger distances between pairs of subject images implies a larger recognition rank for that same pair of images, thus confirming that the subject is harder to recognize.","PeriodicalId":121249,"journal":{"name":"2003 Conference on Computer Vision and Pattern Recognition Workshop","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123861541","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: 83

Drawing Accurate Ground Plans Using Optical Triangulation Data 使用光学三角测量数据绘制精确的地面平面图

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10009

Kevin Cain, Philippe Martinez

引用次数: 1

A Multi Target Track Before Detect Application 一种多目标检测前跟踪的应用

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10100

Y. Boers, J. Driessen, F. Verschure, W. Heemels, A. Juloski

引用次数: 25

Automatic 3D modeling of archaeological objects 考古对象的自动3D建模

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10006

M. Andreetto, N. Brusco, G. Cortelazzo

引用次数: 14

A Factorization Approach for Activity Recognition 一种活动识别的因子分解方法

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10040

A. Roy-Chowdhury, R. Chellappa

{"title":"A Factorization Approach for Activity Recognition","authors":"A. Roy-Chowdhury, R. Chellappa","doi":"10.1109/CVPRW.2003.10040","DOIUrl":"https://doi.org/10.1109/CVPRW.2003.10040","url":null,"abstract":"Understanding activities arising out of the interactions of a configuration of moving objects is an important problem in video understanding, with applications in surveillance and monitoring. A special situation is when the objects are small enough to be represented as points on a 2D plane. In this paper, we introduce a novel method of representing the activity by the deformations of the point configuration in a properly defined shape space. Instead of inferring about the activity directly from the motion tracks of the individual points, we propose to model an activity by the polygonal shape formed by joining the locations of these point masses at any time t, and its deformation as the activity unfolds. Given the locations of the 2D points over a sequence of frames in the video, the factorization theorem for matrices is used to obtain a set of basis shapes for each activity. An unknown activity can now be recognized by projecting onto these basis shapes. Also, once a specific activity is recognized, the deviations from it can be modeled by the deformations from the basis shape. This is used to identify an abnormal activity. We demonstrate the applicability of our algorithm using real-life video sequences in an airport surveillance environment. We are able to identify the major activities that take place in that setting and detect abnormal ones.","PeriodicalId":121249,"journal":{"name":"2003 Conference on Computer Vision and Pattern Recognition Workshop","volume":"24 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113938395","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: 39

Comparative Studies of Line-based Panoramic Camera Calibration 基于线的全景相机标定的比较研究

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10086

F. Huang, Shou-Kang Wei, R. Klette

引用次数: 13

Image Based Hand Tracking via Interacting Multiple Model and Probabilistic Data Association (IMM-PDA) Algorithm 基于交互多模型和概率数据关联(IMM-PDA)算法的图像手部跟踪

2003 Conference on Computer Vision and Pattern Recognition Workshop Pub Date : 2003-06-16 DOI: 10.1109/CVPRW.2003.10050

Shunguang Wu, L. Hong, Francis K. H. Quek

引用次数: 4