[Paper] Face Recognition in Crowded Environmental Using FSIF and Incremental Predictive LDA

Abstract

This paper presents a new approach for recognizing face images having much lower quality in terms of low resolution and contrast than that of the training face images. The input images also contain many faces having multi poses variations because the images were captured under different lighting, sensor, and camera angle. The difficulties of this system are not only in face detection process but also in the recognition process. To handle the difficulties, the improvement of Haar-Like features based face and the Fusion of Scale Invariant Features (FSIF) based classifier are employed, respectively. In addition, the FSIF is integrated with the Incremental Predictive Linear Discriminant Analysis (IPDLDA) for decreasing the time computation of direct FSIF based classification technique. The proposed method can overcome the mentioned difficulties which is shown by high enough recognition rate compared to stand alone FSIF and SIFT-based methods with less than 2 second recognition time.