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21 February 2014 Study and application of body shape recognition based on depth image
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Depth images have advantages of simple processing, fog penetration, and little affection by light, thus a body shape detection algorithm based on depth image was proposed to judge personnel evacuation. This study started by making body shape dataset using a depth sensor, then extracting the HOG-depth feature. The best parameters were found, including the range of gradient direction and the number of bins. Next step was to train and classify the body shape dataset using different classifiers, and gentle Adaboost algorithm based on CART weak classifiers got the best result. Then we discussed the effect of traversal method of sliding window, and found a better pixel number of every moving step. At last, the intellectualized control method under actual personnel evacuating situation was completed from the view of software implementation.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yu-chong Han, Jun Qin, Yu-nong Li, Jun-jun Tao, and Qin Fei "Study and application of body shape recognition based on depth image", Proc. SPIE 9142, Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics: Optical Imaging, Remote Sensing, and Laser-Matter Interaction 2013, 91420J (21 February 2014);


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