Báo cáo hóa học: " Research Article Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 374528 19 pages doi 2008 374528 Research Article Integrated Detection Tracking and Recognition of Faces with Omnivideo Array in Intelligent Environments Kohsia S. Huang and Mohan M. Trivedi Computer Vision and Robotics Research CVRR Laboratory University of California San Diego 9500 Gilman Drive MC 0434 La Jolla CA 92093 USA Correspondence should be addressed to Kohsia S. Huang kshuang@ Received 1 February 2007 Revised 11 August 2007 Accepted 25 November 2007 Recommended by Maja Pantic We present a multilevel system architecture for intelligent environments equipped with omnivideo arrays. In order to gain unobtrusive human awareness real-time 3D human tracking as well as robust video-based face detection and tracking and face recognition algorithms are needed. We first propose a multiprimitive face detection and tracking loop to crop face videos as the front end of our face recognition algorithm. Both skin-tone and elliptical detections are used for robust face searching and viewbased face classification is applied to the candidates before updating the Kalman filters for face tracking. For video-based face recognition we propose three decision rules on the facial video segments. The majority rule and discrete HMM DHMM rule accumulate single-frame face recognition results while continuous density HMM CDHMM works directly with the PCA facial features of the video segment for accumulated maximum likelihood ML decision. The experiments demonstrate the robustness of the proposed face detection and tracking scheme and the three streaming face recognition schemes with 99 accuracy of the CDHMM rule. We then experiment on the system interactions with single person and group people by the integrated layers of activity awareness. We also discuss the speech-aided incremental learning of new faces. Copyright 2008 K. S. Huang and M. M. Trivedi. This is an .

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