30 October 2009 A face-recognition algorithm with a confidence evaluation function
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Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74953O (2009) https://doi.org/10.1117/12.832336
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
In this paper a face-recognition algorithm with a confidence evaluation function for batch of SIFT feature is presented. Confidence evaluation function is rarely used in traditional face recognition, which is an important index in future recognition. In our face-recognition algorithm, two main steps are provided, that is primary election and strict identification. Adaboost algorithm can detect rough features to collect candidate face regions, it works as primary election algorithm. SIFT can describe the detail features in the face regions, the confidence evaluation function for batch of SIFT feature is highly distinctive, and it work as strict identification algorithm. This confidence evaluation function is a reliable measurement for matching multi-candidate regions containing invariant features. And, it can also be used in image retrieval, object recognition.
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Jin Liu, Lin Chen, Lei Wang, "A face-recognition algorithm with a confidence evaluation function", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953O (30 October 2009); doi: 10.1117/12.832336; https://doi.org/10.1117/12.832336
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