The Occluded Object Recognition System Using Partial Shape Features

• Main Authors: Hon-Ling Chen, 陳弘齡
• Other Authors: Jwu-Sheng Hu
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/86418199204994329909

碩士 === 國立交通大學 === 電機與控制工程系所 === 95 === In this thesis, an occluded object recognition system based on partial shape feature is proposed and implemented. The foreground image of object is acquired by the background model built by Gaussian Mixture Model method. We applied the simple Edge Detection to obtain the contour of the foreground as the input of the occluded object recognition system. In order to recognize the occluded object, we must split the complete contour to many partial contours. Hence we will overcome the effect of occlusion. We analyze some split technology and compare the advantage and drawback. We propose an improved non-parameter dominant point detection system and experiment. In the recognition stage, we will use hierarchical compared system. After recognize the correct object, we try to find the occluded part of object. Lastly, we list the results of experiments and discuss the advance of the system.