Feature distribution modelling techniques for 3D face recognition
| Type of publication: | Journal paper |
| Citation: | McCool_PRL_2010 |
| Journal: | Pattern Recognition Letters |
| Volume: | 31 |
| Year: | 2010 |
| Pages: | 1324-1330 |
| Abstract: | This paper shows that Hidden Markov Models (HMMs) can be effectively ap- plied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experi- ments conducted on the Face Recognition Grand Challenge database show that the Equal Error Rate can be reduced from 0.88% for the GMM technique to 0.36% for the best HMM approach. |
| Keywords: | 3D face recognition, Face, Face Recognition, Feature Distribution Modelling, GMM, HMM |
| Projects: |
Idiap MOBIO |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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