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Face Recognition Robust to Local Distortion and Partial Occlusion

Face Recognition Robust to Local Distortion and Partial Occlusion

Jongsun Kim, Juneho Yi, Matthew Turk

 

Overview

This research features an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of "recognition by parts."