Abstract | ||
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In this paper, we propose a spectral descriptor for shapes of objects. The method relies on transforming the 2D objects into 3D space; distance transform and scale space theory is used to transform objects into 3D space. Spherical harmonics of the voxel grid are used to obtain shape descriptors. The proposed methods are compared against two existing methods which use spherical harmonics for shape based retrieval of images. Comparison is done based on ranking of images which is articulated in recall-precision curves. MPEG-7 Still Images Content Set is used for performing experiments. Experimental results show that the performance of the proposed descriptor is significantly better than other methods in the same category. |
Year | DOI | Venue |
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2010 | 10.3233/ICA-2010-0335 | Integrated Computer-Aided Engineering |
Keywords | Field | DocType |
recall-precision curve,proposed descriptor,spectral shape descriptor,existing method,spectral descriptor,shape descriptors,spherical harmonic,scale space theory,content set,feature extraction | Voxel,Computer vision,Pattern recognition,Ranking,Spherical harmonics,Scale space,Feature extraction,Distance transform,Artificial intelligence,Spectral shape analysis,Mathematics,Grid | Journal |
Volume | Issue | ISSN |
17 | 2 | 1069-2509 |
Citations | PageRank | References |
3 | 0.40 | 13 |
Authors | ||
6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Atul Sajjanhar | 1 | 154 | 19.00 |
Guojun Lu | 2 | 1965 | 82.04 |
Dengsheng Zhang | 3 | 2462 | 100.00 |
Jingyu Hou | 4 | 181 | 16.93 |
Wanlei Zhou | 5 | 2295 | 189.31 |
Yi-ping Phoebe Chen | 6 | 1060 | 128.42 |