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The Feature Extraction and the Description of Point Cloud Image Based on S-NARF Algorithm |
LÜ Qiang, WANG Xiaolong, LIU Feng, NI Peipei |
Department of Control Engineering, Academy of Armored Forces Engineering, Beijing 100072, China |
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Abstract: In view of the slow operation speed of the NARF algorism and the limitations of the extracting border feature, a new algorism is proposed to calculate the 3D NARF by using a local coordinate system with origin in the SIFT keypoint position. Firstly, the feature of the point cloud image is detected, a DoG3D operator is built to extract the 3D SIFT keypoints, then the feature of the keypoints is described, in a local coordinate system with origin in the keypoint position of the corresponding range image, the patches are projected to the design star shaped patterns with beams of equal angle interval within them according to the image resolution. The values of the descriptor vector elements are calculated by using the cells that lie under the beam, to form the given dimension descriptor. Finally, the experiments based on the point cloud obtained by the RGB-D sensor show that the algorithm can speed up the operation and the extracted feature is more general than that extracted by previous algorithms, by retaining more typical and distinct features of the descriptors.
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Received: 28 January 2013
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