A face-recognition algorithm with a confidence evaluation function
Jin Liu, Lin Chen, Lei Wang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
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.