Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)最新文献_第5页

Tracking a person with 3-D motion by integrating optical flow and depth 通过整合光流和深度来跟踪具有三维运动的人

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840656

R. Okada, Y. Shirai, J. Miura

引用次数: 42

Face recognition algorithms as models of human face processing 人脸识别算法作为人脸处理的模型

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840689

A. O’Toole, Y. Cheng, B. Ross, Heather A. Wild, P. Phillips

引用次数: 15

Bimodal emotion recognition 双峰情绪识别

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840655

L. D. Silva, Pei Chi Ng

引用次数: 126

Crane gesture recognition using pseudo 3-D hidden Markov models 基于伪三维隐马尔可夫模型的起重机手势识别

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840665

Stefan Müller, S. Eickeler, G. Rigoll

引用次数: 13

Estimation of the illuminant colour from human skin colour 根据人的肤色估计光源颜色

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840613

M. Störring, H. J. Andersen, E. Granum

{"title":"Estimation of the illuminant colour from human skin colour","authors":"M. Störring, H. J. Andersen, E. Granum","doi":"10.1109/AFGR.2000.840613","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840613","url":null,"abstract":"Colour is an important and useful feature for object tracking and recognition in computer vision. However, it has the difficulty that the colour of the object changes if the illuminant colour changes. But under known illuminant colour it becomes a robust feature. There are more and more computer vision applications tracking humans, for example in interfaces for human computer interaction or automatic camera men, where skin colour is an often-used feature. Hence, it would be of significant importance to know the illuminant colour in such applications. This paper proposes a novel method to estimate the current illuminant colour from skin colour observations. The method is based on a physical model of reflections, the assumption that illuminant colours are located close to the Planckian locus, and the knowledge about the camera parameters. The method is empirically tested using real images. The average estimation error of the correlated colour temperature is as small as 180 K. Applications are for example in colour-based tracking to adapt to changes in lighting and in visualisation to re-render image colours to their appearance under canonical viewing conditions.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124125704","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: 53

Support vector regression and classification based multi-view face detection and recognition 基于支持向量回归和分类的多视图人脸检测与识别

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840650

Yongmin Li, S. Gong, H. Liddell

{"title":"Support vector regression and classification based multi-view face detection and recognition","authors":"Yongmin Li, S. Gong, H. Liddell","doi":"10.1109/AFGR.2000.840650","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840650","url":null,"abstract":"A support vector machine-based multi-view face detection and recognition framework is described. Face detection is carried out by constructing several detectors, each of them in charge of one specific view. The symmetrical property of face images is employed to simplify the complexity of the modelling. The estimation of head pose, which is achieved by using the support vector regression technique, provides crucial information for choosing the appropriate face detector. This helps to improve the accuracy and reduce the computation in multi-view face detection compared to other methods. For video sequences, further computational reduction can be achieved by using a pose change smoothing strategy. When face detectors find a face in frontal view, a support vector machine-based multi-class classifier is activated for face recognition. All the above issues are integrated under a support vector machine framework. Test results on four video sequences are presented, among them the detection rate is above 95%, recognition accuracy is above 90%, average pose estimation error is around 10/spl deg/, and the full detection and recognition speed is up to 4 frames/second on a Pentium II 300 PC.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131521216","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: 276

Comparative evaluation of face sequence matching for content-based video access 基于内容的视频访问人脸序列匹配的比较评价

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840629

S. Satoh

{"title":"Comparative evaluation of face sequence matching for content-based video access","authors":"S. Satoh","doi":"10.1109/AFGR.2000.840629","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840629","url":null,"abstract":"The paper presents a comparative evaluation of matching methods of face sequences obtained from actual videos. Face information is quite important in videos, especially in news programs, dramas, and movies. Accurate face sequence matching enables many multimedia applications including content-based face retrieval, automated face annotation, video authoring, etc. However, face sequences in videos are subject to variation in lighting condition, pose, facial expression, etc., which cause difficulty in face matching. In order to cope with this problem, several face sequence matching methods are proposed by extending face still image matching, traditional pattern recognition, and recent pattern recognition techniques. They are expected to be applicable to face sequences extracted from actual videos. The performance of these methods is evaluated as the accuracy of face sequence annotation using the methods. The accuracy is evaluated using a considerable amount of actual drama videos. The evaluation results reveal merits and demerits of these methods, and indicate future research directions of face matching for videos.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116972306","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: 89

Learning-based approach to real time tracking and analysis of faces 基于学习的人脸实时跟踪和分析方法

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840618

Vinay P. Kumar, T. Poggio

{"title":"Learning-based approach to real time tracking and analysis of faces","authors":"Vinay P. Kumar, T. Poggio","doi":"10.1109/AFGR.2000.840618","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840618","url":null,"abstract":"This paper describes a trainable system capable of tracking faces and facial features like eyes and nostrils and estimating basic mouth features such as degrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on an optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124333615","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: 62

Real-time multiple face detection using active illumination 使用主动照明的实时多人脸检测

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840605

C. Morimoto, M. Flickner

引用次数: 79

Detection and tracking of facial features in real time using a synergistic approach of spatio-temporal models and generalized Hough-transform techniques 利用时空模型和广义霍夫变换技术的协同方法实时检测和跟踪面部特征

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840621

A. Schubert

{"title":"Detection and tracking of facial features in real time using a synergistic approach of spatio-temporal models and generalized Hough-transform techniques","authors":"A. Schubert","doi":"10.1109/AFGR.2000.840621","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840621","url":null,"abstract":"The proposed algorithm requires the description of the facial features as 3D-polygons (optionally extended by additional intensity information) which are assembled in a 3D-model of the head provided for in separate data files. Detection is achieved by using a special implementation of the generalized Hough transform (GHT) for which the forms are generated by projecting the 3D-model into the image plane. In the initialization phase a comparatively wide range of relative positions and attitudes between head and camera has to be tested for. Aiming for illumination-independence, only information about the sign of the difference between the expected intensities on both sides of the edge of the polygons may be additionally used in the GHT. Once a feature is found, further search for the remaining features can be restricted by the use of the 3D-model. The detection of a minimum number of features starts the tracking phase which is performed by using an extended Kalman filter (EKF) and assuming a first- or second-order dynamical model for the state variables describing the position and the attitude of the head. Synergistic advantages between GHT and EKF can be realized since the EKF and the projection into the image plane yield a rather good prediction of the forms to be detected by the GHT. This reduces considerably the search space in the image and in the parameter space. On the other hand the GHT offers a solution to the matching problem between image and object features. During the tracking phase the GHT can be further enhanced by monitoring the actual intensities along the edges of the polygons, their assignment to the corresponding 3D-object features, and their use for feature selection during the accumulation process. The algorithm runs on a dual Pentium II 333 MHz with a cycle time of 40 ms in real time.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129818713","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: 14