淡江大學機構典藏:Item 987654321/55038
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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/55038


    Title: Robust Face Tracking Control of a Mobile Robot Using Self-Tuning Kalman Filter and Echo State Network
    Authors: Tsai, Chi-yi;Xavier Dutoit;Song, Kai-tai;Hendrik Van Brussel;Marnix Nutti
    Contributors: 淡江大學電機工程學系
    Keywords: Visual tracking control;visual state estimation;echo state network;face tracking;illumination variation
    Date: 2010-07
    Issue Date: 2011-08-09 20:29:51 (UTC+8)
    Publisher: Hoboken: Wiley-Blackwell Publishing, Inc.
    Abstract: This paper presents a novel design of face tracking algorithm and visual state estimation for a mobile robot face tracking interaction control system. The advantage of this design is that it can track a user's face under several external uncertainties and estimate the system state without the knowledge about target's 3D motion-model information. This feature is helpful for the development of a real-time visual tracking control system. In order to overcome the change in skin color due to light variation, a real-time face tracking algorithm is proposed based on an adaptive skin color search method. Moreover, in order to increase the robustness against colored observation noise, a new visual state estimator is designed by combining a Kalman filter with an echo state network-based self-tuning algorithm. The performance of this estimator design has been evaluated using computer simulation. Several experiments on a mobile robot validate the proposed control system.
    Relation: Asian Journal of Control 12(4), pp.488-509
    DOI: 10.1002/asjc.204
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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