Face recognition with correlation filters designed with multi-objective combinatorial optimization

3:25 pm - 3:50 pm 24 Thursday

Track

Pattern recognition

A reliable approach for face recognition using composite correlation filters is presented. The filters are designed by combining several face images which are chosen by means of multi-objective combinatorial optimization. Given a vast search space of available face images, an iterative algorithm is used to synthesize a filter bank with an optimized performance in terms of several performance metrics. Computer simulation results obtained with the proposed method for face recognition in noisy scenes are discussed and compared in terms of recognition performance with existing state-of-the-art methods.

Speaker:
Adrian Cuevas