标题:REAL-TIME MULTI-CANDIDATES FUSION BASED HEAD TRACKING ON KINECT DEPTH SEQUENCE
作者:Yang, Zhiting; Yang, Yang; Liu, Yun-Xia
通讯作者:Yang, Yang
作者机构:[Yang, Zhiting; Yang, Yang] Shandong Univ, Sch Informat Sci & Engn, Jinan, Peoples R China.; [Liu, Yun-Xia] Shandong Univ, Sch Control Sci & Engn, J 更多
会议名称:IEEE International Conference on Acoustics, Speech, and Signal Processing
会议日期:MAR 20-25, 2016
来源:2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS
出版年:2016
卷:2016-May
页码:1511-1515
DOI:10.1109/ICASSP.2016.7471929
关键词:Kinect; Head tracking; Multi-candidates fusion; Two-stage searching;; Early termination
摘要:Considering depth images are robust to illumination variations with complex backgrounds, the paper developed a real-time head tracking system with one Kinect camera. Distance transform is applied to pre-processed depth frames to further reduce the effect of appearance deformation. A multi-candidates fusion strategy is proposed for template updating that assures head representation robustness. Two stage template matching is adopted for computational efficiency in the searching procedure. In addition, an early termination criterion for template updating is presented to reliably improve the tracking accuracy. Abundant experimental results on our depth database demonstrate that the proposed method performs favorably against state-of the-art methods in terms of robustness, accuracy, and efficiency.
收录类别:CPCI-S;EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973400192&doi=10.1109%2fICASSP.2016.7471929&partnerID=40&md5=c71204d8c92f06f30a4a85877280bd1b
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