Face and Ear: A Bimodal Identification System
In this paper, several configurations for a hybrid face/ear recognition system are investigated. The system is based on IFS (Iterated Function Systems) theory that are applied on both face and ear resulting in a bimodal architecture. One advantage is that the information used for the indexing and recognition task of face/ear can be made local, and this makes the method more robust to possible occlusions. The amount of information provided by each component of the face and the ear image has been assessed, first independently and then jointly. At last, results underline that the system significantly outperforms the existing approaches in the state of the art.
KeywordsFace Recognition Face Image Iterate Function System Face Component Average Approximation Error
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