Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems最新文献_第2页

Robust facial feature point detection under nonlinear illuminations 非线性光照下鲁棒人脸特征点检测

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938927

J. Lai, P. Yuen, Wen Chen, S. Lao, M. Kawade

{"title":"Robust facial feature point detection under nonlinear illuminations","authors":"J. Lai, P. Yuen, Wen Chen, S. Lao, M. Kawade","doi":"10.1109/RATFG.2001.938927","DOIUrl":"https://doi.org/10.1109/RATFG.2001.938927","url":null,"abstract":"Addresses the problem of facial feature point detection under different lighting conditions. Our goal is to develop an efficient detection algorithm, which is suitable for practical applications. The problems that we need to overcome include (1) high detection accuracy, (2) low computational time and (3) nonlinear illumination. An algorithm is developed and reported in the paper. One of the key factors affecting the performance of feature point detection is the accuracy in locating face boundary. To solve this problem, we propose to make use of skin color, lip color and also the face boundary information. The basic idea to overcome the nonlinear illumination is that, each person shares the same/similar facial primitives, such as two eyes, one nose and one mouth. So the binary images of each person should be similar. Again, if a binary image (with appropriate thresholding) is obtained from the gray scale image, the facial feature points can also be detection easily. To achieve this, we propose to use the integral optical density (IOD) on face region. We propose to use the average IOD to detect feature windows. As all the above-mentioned techniques are simple and efficient, the proposed method is computationally effective and suitable for practical applications. 743 images from the Omron database with different facial expressions, different glasses and different hairstyle captured indoor and outdoor have been used to evaluate the proposed method and the detection accuracy is around 86%. The computational time in Pentium III 750 MHz using matlab for implementation is less than 7 seconds.","PeriodicalId":355094,"journal":{"name":"Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129190157","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: 31

Nonlinear mapping from multi-view face patterns to a Gaussian distribution in a low dimensional space 从多视图人脸模式到低维空间高斯分布的非线性映射

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938909

Stan Z. Li, Rong Xiao, ZeYu Li, HongJiang Zhang

{"title":"Nonlinear mapping from multi-view face patterns to a Gaussian distribution in a low dimensional space","authors":"Stan Z. Li, Rong Xiao, ZeYu Li, HongJiang Zhang","doi":"10.1109/RATFG.2001.938909","DOIUrl":"https://doi.org/10.1109/RATFG.2001.938909","url":null,"abstract":"We investigate into a nonlinear mapping by which multi-view face patterns in the input space are mapped into invariant points in a low dimensional feature space. The invariance to both illumination and view is achieved in two-stages. First, a nonlinear mapping from the input space to a low dimensional feature space is learned from multi-view face examples to achieve illumination invariance. The illumination invariant feature points of face patterns across views are on a curve parameterized by the view parameter, and the view parameter of a face pattern can be estimated from the location of the feature point on the curve by using least squares fit. Then the second nonlinear mapping, which is from the illumination invariant feature space to another feature space of the same dimension, is performed to achieve invariance to both illumination and view. This amounts to do a normalization based on the view estimate. By the two stage nonlinear mapping, multi-view face patterns are mapped to a zero mean Gaussian distribution in the latter feature space. Properties of the nonlinear mappings and the Gaussian face distribution are explored and supported by experiments.","PeriodicalId":355094,"journal":{"name":"Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems","volume":"500 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120869564","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: 17

A stabilized adaptive appearance changes model for 3D head tracking 一种用于三维头部跟踪的稳定自适应外观变化模型

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938928

Eisuke Adachi, Takio Kurita, N. Otsu

引用次数: 19

Learning visual models of social engagement 学习社会参与的视觉模型

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938923

B. Singletary, Thad Starner

{"title":"Learning visual models of social engagement","authors":"B. Singletary, Thad Starner","doi":"10.1109/RATFG.2001.938923","DOIUrl":"https://doi.org/10.1109/RATFG.2001.938923","url":null,"abstract":"We introduce a face detector for wearable computers that exploits constraints in face scale and orientation imposed by the proximity of participants in near social interactions. Using this method we describe a wearable system that perceives \"social engagement,\" i.e., when the wearer begins to interact with other individuals. Our experimental system proved >90% accurate when tested on wearable video data captured at a professional conference. Over 300 individuals were captured during social engagement, and the data was separated into independent training and test sets. A metric for balancing the performance of face detection, localization, and recognition in the context of a wearable interface is discussed. Recognizing social engagement with a user's wearable computer provides context data that can be useful in determining when the user is interruptible. In addition, social engagement detection may be incorporated into a user interface to improve the quality of mobile face recognition software. For example, the user may cue the face recognition system in a socially graceful way by turning slightly away and then toward a speaker when conditions for recognition are favorable.","PeriodicalId":355094,"journal":{"name":"Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132722803","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: 6

Sample-based synthesis of talking heads 基于样本的说话头合成

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938903

H. Graf, E. Cosatto

引用次数: 12

Using the active appearance algorithm for face and facial feature tracking 利用主动外观算法对人脸和面部特征进行跟踪

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938912

Jörgen Ahlberg

引用次数: 61

Real-time stereo tracking of multiple moving heads 多个移动头部的实时立体跟踪

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938910

R. Luo, Yan Guo

引用次数: 17

Efficient real-time face tracking in wavelet subspace 基于小波子空间的高效实时人脸跟踪

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938919

R. S. Feris, Roberto M. Cesar, V. Kruger

引用次数: 34

Reconstruction of movies of facial expressions 面部表情电影的重建

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938904

G. Moiza, A. Tal, I. Shimshoni, D. Barnett, Y. Moses

引用次数: 4

Head gestures for computer control 头部手势用于计算机控制

Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems Pub Date : 2001-07-13 DOI: 10.1109/RATFG.2001.938911

R. Kjeldsen

引用次数: 55