Abstract
Estimation of hands and arms motion in a car driving by utilizing a depth image sensor, specifically, KINECT of Microsoft Xbox 360, has been proposed. Compared with conventional researches using ordinary vision sensor, depth sensor provides rich information for the hands and arms in the scene. Especially, arms’ regions detected by the depth sensor have been utilized to estimate the hands and arms motion more accurately than the conventional researches. As well as the increasing accuracy of the hands and arms region extraction, this paper proposes to incorporate some particles intentionally switching the left and the right of the hands in a framework of particle filter. This idea reduce the mistaken (opposite) determination of left and right and it will increase the opportunity to recover automatically from the opposite determination. Experiments over the recorded videos of vision and depth under a driving simulator environment show the efficiency of the proposed method.
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References
Doucet, A., de Freitas, N., Gordon, N.J. (eds.): Sequential Monte Carlo Methods in Practice. Springer, New York (2001)
Ikoma, N.: Tracking of Car Driver’s Hands in Depth Image Sensor by Particle Filter. In: 8th International Conference on Innovative Computing, Information and Control (ICICIC 2013) (2013) (to appear)
Ikoma, N., Ito, T.: GPGPU implementation of visual tracking by particle filter with pixel ratio likelihood. In: 2012 IEEE/SICE International Symposium on System Integration (SII), pp. 889–894 (2012)
Ikoma, N.: Visual tracking of both hands of car driver by particle filter. In: 5th Int’l Conf. on Soft Computing and Intelligent Systems and 11th Int’l Sympo. on advanced Intelligent Systems (SCIS & ISIS 2010), pp. 1547–1552 (2010)
Ikoma, N.: Real-Time Motion Estimation of Car Driver’s Hands and Arm’s Direction in Vision under Possible Mutual Occlusion by Particle Filter. In: 6th Int’l Conf. on Soft Computing and Intelligent Systems and 13th Int’l Sympo. on advanced Intelligent Systems (SCIS & ISIS 2012), pp. 701–704 (2012)
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Ikoma, N. (2014). Hands and Arms Motion Estimation of a Car Driver with Depth Image Sensor by Using Particle Filter. In: Rhee, SY., Park, J., Inoue, A. (eds) Soft Computing in Machine Learning. Advances in Intelligent Systems and Computing, vol 273. Springer, Cham. https://doi.org/10.1007/978-3-319-05533-6_8
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DOI: https://doi.org/10.1007/978-3-319-05533-6_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05532-9
Online ISBN: 978-3-319-05533-6
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