Feature subspace determination in video-based mismatched face recognition
In video-based face recognition (FR) applications such as surveillance security, the resolution of a facial image could significantly impact the reliability of recognition system. In most practical FR applications, it is reasonable to assume that the face resolution used during training is higher than the resolution used during the identification or verification process. This dimensional mismatch negatively impacts the performance of the traditional subspace recognition solutions. To address resolution mismatch problem, this paper introduces a novel estimation method capable of determining feature subspace of the lower resolution probe given an eigenspace pre-trained with higher resolution facial images. The effectiveness of the proposed solution has been successfully tested on standard CMU PIE face dataset. Experimental results and comparative evaluations provided in this work demonstrate the benefits of the proposed solution.