Stereo vision in detecting human motion is an emerging research for automation, robotics, and sports science field due to the advancement of imaging sensors and information technology. The difficulty of human motion detection and tracking is relatively complex when it is applied to uncontrolled environment. In this paper, a hybrid filter approach is proposed to detect human motion in the stereo vision. The hybrid filter approach integrates Gaussian filter and median filter to reduce the coverage of shadow and sudden change of illumination. In addition, sequential thinning and thickening morphological method is used to construct the skeleton model. The proposed hybrid approach is compared with the normalized filter. As a result, the proposed approach produces better skeleton model with less influential effect on shadow and illumination. The output results of the proposed approach can show up to 86% of average accuracy matched with skeleton model. In addition, obtains approximately 94% of sensitivity measurement in the stereo vision. The proposed approach using hybrid filter and sequential morphology could improve the performance of the detection in the uncontrolled environment.


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    Title :

    Stereo Vision Human Motion Detection and Tracking in Uncontrolled Environment


    Contributors:

    Publication date :

    2018-06-01


    Remarks:

    doi:10.12928/telkomnika.v16i3.9033
    TELKOMNIKA (Telecommunication Computing Electronics and Control); Vol 16, No 3: June 2018; 955-964 ; 2302-9293 ; 1693-6930 ; 10.12928/telkomnika.v16i3



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




    Stereo vision human motion detection and tracking in uncontrolled environment

    Chan, Bunseng / Lim, King Hann / Gopal, Lenin et al. | BASE | 2018

    Free access