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Ear Recognition Using SIFT Keypoint Matching
| Content Provider | Semantic Scholar |
|---|---|
| Author | Dong, Xin |
| Abstract | In this paper, we present a novel algorithm for 3D ear recognition. The basic idea is to rotate each 3D point cloud representing an individual’s ear around the x, y or z axes, respectively generating multiple 2.5D images at each step of the rotation. Then we use SIFT descriptors to extract and describe the features of human ears. The test ear images are recognized by the application of a new weighted keypoint matching algorithm. Experimental results show that this method is both accurate and efficient. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ipcsit.com/vol44/027-ICCAE2011-A00479.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |