2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443)最新文献_第2页

Manifold of facial expression 面部表情的多样性

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240820

Ya Chang, Changbo Hu, M. Turk

引用次数: 139

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240830

A. Johnson, Jie Sun, A. Bobick

引用次数: 32

Absolute head pose estimation from overhead wide-angle cameras 从头顶广角摄像机估计绝对头部姿势

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240829

Ying-li Tian, L. Brown, J. Connell, Sharath Pankanti, A. Hampapur, A. Senior, R. Bolle

引用次数: 52

Fully automatic upper facial action recognition 全自动上面部动作识别

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240843

Ashish Kapoor, Yuan Qi, Rosalind W. Picard

{"title":"Fully automatic upper facial action recognition","authors":"Ashish Kapoor, Yuan Qi, Rosalind W. Picard","doi":"10.1109/AMFG.2003.1240843","DOIUrl":"https://doi.org/10.1109/AMFG.2003.1240843","url":null,"abstract":"We provide a new fully automatic framework to analyze facial action units, the fundamental building blocks of facial expression enumerated in Paul Ekman's facial action coding system (FACS). The action units examined here include upper facial muscle movements such as inner eyebrow raise, eye widening, and so forth, which combine to form facial expressions. Although prior methods have obtained high recognition rates for recognizing facial action units, these methods either use manually preprocessed image sequences or require human specification of facial features; thus, they have exploited substantial human intervention. We present a fully automatic method, requiring no such human specification. The system first robustly detects the pupils using an infrared sensitive camera equipped with infrared LEDs. For each frame, the pupil positions are used to localize and normalize eye and eyebrow regions, which are analyzed using PCA to recover parameters that relate to the shape of the facial features. These parameters are used as input to classifiers based on support vector machines to recognize upper facial action units and all their possible combinations. On a completely natural dataset with lots of head movements, pose changes and occlusions, the new framework achieved a recognition accuracy of 69.3% for each individual AU and an accuracy of 62.5% for all possible AU combinations. This framework achieves a higher recognition accuracy on the Cohn-Kanade AU-coded facial expression database, which has been previously used to evaluate other facial action recognition system.","PeriodicalId":388409,"journal":{"name":"2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114067798","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: 150

Human body tracking with auxiliary measurements 带有辅助测量的人体跟踪

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240832

M. Lee, I. Cohen

引用次数: 22

Component-based LDA method for face recognition with one training sample 基于组件的单训练样本人脸识别LDA方法

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240833

Jian Huang, P. Yuen, Wensheng Chen, J. Lai

{"title":"Component-based LDA method for face recognition with one training sample","authors":"Jian Huang, P. Yuen, Wensheng Chen, J. Lai","doi":"10.1109/AMFG.2003.1240833","DOIUrl":"https://doi.org/10.1109/AMFG.2003.1240833","url":null,"abstract":"Many face recognition algorithms/systems have been developed in the last decade and excellent performances are also reported when there is sufficient number of representative training samples. In many real-life applications, only one training sample is available. Under this situation, the performance of existing algorithms will be degraded dramatically or the formulation is incorrect, which in turn, the algorithm cannot be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples, but also consider the face detection localization error while training. After that, we employ a sub-space LDA method, which is tailor-made for small number of training samples, for the local feature projection to maximize the discrimination power. Finally, combining the contributions of each local feature draws the recognition decision. FERET database is used for evaluating the proposed method and results are encouraging.","PeriodicalId":388409,"journal":{"name":"2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125044212","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: 54

Multi-modal face tracking using Bayesian network 基于贝叶斯网络的多模态人脸跟踪

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240835

Fang Liu, X. Lin, S. Li, Yuanchun Shi

引用次数: 30

Inference of human postures by classification of 3D human body shape 基于三维人体形态分类的人体姿态推断

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240827

I. Cohen, Hongxia Li

引用次数: 154

CSLDS: Chinese sign language dialog system 中文手语对话系统

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240850

Yiqiang Chen, Wen Gao, Gaolin Fang, Changshui Yang, Zhaoqi Wang

引用次数: 28

A quantified study of facial asymmetry in 3D faces 三维人脸面部不对称性的量化研究

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443) Pub Date : 2003-10-17 DOI: 10.1109/AMFG.2003.1240847

Yanxi Liu, J. Palmer

引用次数: 41