| Summary: | 碩士 === 國立交通大學 === 電控工程研究所 === 99 === In recent years, research works of three dimensional object recognition in point cloud data become more and more popular. Appearance-based features, such as silhouettes of objects, will directly affect the recognition efficiency in different
positions with various angles. To tackle this problem, this thesis proposes a recognition system with two-feature integration. One is the Fourier descriptor of the contour in a range image, and the other is the structure descriptor extracted from point clouds. The Fourier descriptor is used to identify an object in the far distance.
Additionally, a method of view-angle interpolation is proposed to increase the correct recognition rate. The structure descriptor is used to recognize an object when closing to the object, since the contour information lacks the ability to describe the object.
Furthermore, a strategy of proposed method is presented to select the appropriate feature for object recognition. Ten different control towers are used to verify the performance of the proposed approach. The experimental results show that the proposed system performs better than the method using only feature of range image or feature of point clouds data across the entire distance range.
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