Improved Light Field Descriptor Using Depth Images for 3D Model Retrieval

doi:10.13190/j.jbupt.2016.04.011

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2016, Vol. 39 ›› Issue (4): 56-59.doi: 10.13190/j.jbupt.2016.04.011

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Improved Light Field Descriptor Using Depth Images for 3D Model Retrieval

LI Hai-sheng^1,2, DONG Shui-long^1,2, ZHAO Tian-yu^1,2, CAI Qiang^1,2, DU Jun-ping³

1. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;
2. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing 100048, China;
3. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2015-12-29 Online:2016-08-28 Published:2016-08-28

Abstract

Abstract: Due to the problem of light field descriptor lacking spatial information of 3D model, and the problem of little projection of PANORAMA descriptor, a 3D model retrieval algorithm combining depth image was proposed. The depth images are used to improve light field descriptor. Discrete wavelet transform features and Zernike moments are extracted from projection views. Then the depth images are clustered to remove redundancy. The random walk algorithm is employed to determine the weight of each cluster. Finally, the retrieval method of PANORAMA is optimized to calculate similarity distance between two 3D models. Results on princeton shape benchmark show that the proposed algorithm can make good use of spatial information of 3D model and improve the accuracy of retrieval.

Key words: depth image, light field descriptor, PANORAMA descriptor, 3D model retrieval

CLC Number:

TP391.41

LI Hai-sheng, DONG Shui-long, ZHAO Tian-yu, CAI Qiang, DU Jun-ping. Improved Light Field Descriptor Using Depth Images for 3D Model Retrieval[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 39(4): 56-59.

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Improved Light Field Descriptor Using Depth Images for 3D Model Retrieval

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