Face recognition with DAISY descriptors
Proceedings of the 12th ACM workshop on Multimedia and security
Stylized textile image pattern classification using SIFT keypoint histograms
Edutainment'11 Proceedings of the 6th international conference on E-learning and games, edutainment technologies
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This paper investigates the possibility that uses Scale-Invariance Feature Transform (SIFT) feature for face identification. However, it is impossible to employ these SIFT keys,i.e. feature vectors, for identification directly, due to the space incompatible of such SIFT keys. To this end, the Bag-of-words (Bow) vector quantization introduced from scene or text classification is conducted for unifying them. And a novel distance, Cauchy-Schwartz Inequality Distance (CSID), is performed for determining which cluster each keypoint of image belongs to after quantization, in order to compose a histogram vector as our feature. To summarize, this approach solves the problem of space incompatible and avoids a high computation that gives rises to a "dimensional curse". The experiment shows a reasonable result using SVM classifier by ORL database.