| Summary: | 碩士 === 國立交通大學 === 電控工程研究所 === 100 === This thesis proposes an intelligent human detection system based on depth information generated by Kinect to find out humans from a sequence of images and resolve occlusion problems. The system is divided into three parts, including region-of-interest (ROI) selection, feature extraction and human recognition. First, the histogram projection and connected component labeling are applied to select the ROIs according to the property that human would present vertically in general. Then, normalize the ROIs based on the distances between objects and camera and extract the human shape feature by the edge detection and distance transformation to obtain the distance image. Finally, the chamfer matching is used to search possible parts of human body under component-based concept, and then shape recognition is implemented by neural network according to the combination of parts of human body. From the experimental results, the system could detect humans with high accuracy rate and resolve occlusion problems.
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