Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)最新文献_第7页

Exploiting speech/gesture co-occurrence for improving continuous gesture recognition in weather narration 利用语音/手势共现改善天气叙述中的连续手势识别

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840669

Rajeev Sharma, Jiongyu Cai, Srivatsan Chakravarthy, Indrajit Poddar, Y. Sethi

{"title":"Exploiting speech/gesture co-occurrence for improving continuous gesture recognition in weather narration","authors":"Rajeev Sharma, Jiongyu Cai, Srivatsan Chakravarthy, Indrajit Poddar, Y. Sethi","doi":"10.1109/AFGR.2000.840669","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840669","url":null,"abstract":"In order to incorporate naturalness in the design of human computer interfaces (HCI), it is desirable to develop recognition techniques capable of handling continuous natural gesture and speech inputs. Though many different researchers have reported high recognition rates for gesture recognition using hidden Markov models (HMM), the gestures used are mostly pre-defined and are bound with syntactical and grammatical constraints. But natural gestures do not string together in syntactical bindings. Moreover, strict classification of natural gestures is not feasible. We have examined hand gestures made in a very natural domain, that of a weather person narrating in front of a weather map. The gestures made by the weather person are embedded in a narration. This provides us with abundant data from an uncontrolled environment to study the interaction between speech and gesture in the context of a display. We hypothesize that this domain is very similar to that of a natural human-computer interface. We present an HMM architecture for continuous gesture recognition framework and keyword spotting. To explore the relation between gesture and speech, we conducted a statistical co-occurrence analysis of different gestures with a selected set of spoken keywords. We then demonstrate how this co-occurrence analysis can be exploited to improve the performance of continuous gesture recognition.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"345 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":"115290260","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: 33

Segmenting hands of arbitrary color 分割任意颜色的手

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840673

Xiaojin Zhu, Jie Yang, A. Waibel

{"title":"Segmenting hands of arbitrary color","authors":"Xiaojin Zhu, Jie Yang, A. Waibel","doi":"10.1109/AFGR.2000.840673","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840673","url":null,"abstract":"Hand segmentation is a prerequisite for many gesture recognition tasks. Color has been widely used for hand segmentation. However, many approaches rely on predefined skin color models. It is very difficult to predefine a color model in a mobile application where the light condition may change dramatically over time. We propose a novel statistical approach to hand segmentation based on Bayes decision theory. The proposed method requires no predefined skin color model. Instead it generates a hand color model and a background color model for a given image, and uses these models to classify each pixel in the image as either a hand pixel or a background pixel. Models are generated using a Gaussian mixture model with the restricted EM algorithm. Our method is capable of segmenting hands of arbitrary color in a complex scene. It performs well even when there is a significant overlap between hand and background colors, or when the user wears gloves. We show that the Bayes decision method is superior to a commonly used method by comparing their upper bound performance. Experimental results demonstrate the feasibility of the proposed method.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"164 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":"115545730","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: 172

Dual-state parametric eye tracking 双状态参数眼动追踪

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840620

Ying-li Tian, T. Kanade, J. Cohn

引用次数: 189

Wide-range, person- and illumination-insensitive head orientation estimation 宽范围，人和光照不敏感的头部方向估计

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840632

Ying Wu, K. Toyama

引用次数: 85

Tracking interacting people 跟踪互动的人

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840658

S. McKenna, S. Jabri, Zoran Duric, H. Wechsler

引用次数: 115

Toward real-time human-computer interaction with continuous dynamic hand gestures 向着持续动态手势的实时人机交互方向发展

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840688

Yuanxin Zhu, Haibing Ren, Guangyou Xu, X. Lin

引用次数: 33

Face analysis for the synthesis of photo-realistic talking heads 人脸分析合成逼真的说话头

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840633

H. Graf, E. Cosatto, Tony Ezzat

{"title":"Face analysis for the synthesis of photo-realistic talking heads","authors":"H. Graf, E. Cosatto, Tony Ezzat","doi":"10.1109/AFGR.2000.840633","DOIUrl":"https://doi.org/10.1109/AFGR.2000.840633","url":null,"abstract":"This paper describes techniques for extracting bitmaps of facial parts from videos of a talking person. The goal is to synthesize photo-realistic talking heads of high quality that show picture-perfect appearance and realistic head movements with good lip-sound synchronization. For the synthesis of a talking head, bitmaps of facial parts are combined to form whole heads and then sequences of such images are integrated with audio from a text-to-speech synthesizer. For a seamless integration of facial parts into an animation, their shape and visual appearance must be known with high accuracy. The recognition system has to find not only the locations of facial features, but must also be able to determine the head's orientation and recognize the facial expressions. Our face recognition proceeds in multiple steps, each with an increased precision. Using motion, color and shape information, the head's position and the location of the main facial features are determined first. Then smaller areas are searched with matched filters, in order to identify specific facial features with high precision. From this information a head's 3D orientation is calculated. Facial parts are cut from the image and, using the head's orientation, are warped into bitmaps with 'normalized' orientation and scale.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"14 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":"124452820","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: 47

Audio-visual speaker detection using dynamic Bayesian networks 基于动态贝叶斯网络的视听说话人检测

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840663

A. Garg, V. Pavlovic, James M. Rehg

引用次数: 50

Relevant features for video-based continuous sign language recognition 基于视频的连续手语识别的相关特征

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840672

Britta Bauer, Hermann Hienz

引用次数: 143

Face recognition by support vector machines 基于支持向量机的人脸识别

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580) Pub Date : 2000-03-26 DOI: 10.1109/AFGR.2000.840634

G. Guo, S. Li, K. Chan

引用次数: 611