Robust multi-camera view face recognition

Computer Science – Computer Vision and Pattern Recognition

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

10 pages, 3 figures, IJCA

Scientific paper

This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalization of Linear Discriminant Analysis (LDA) for multi-camera view offline face recognition (verification) system. The generalization of LDA has been extended to establish correlations between the face classes in the transformed representation and this is called canonical covariate. The proposed system uses Gabor filter banks for characterization of facial features by spatial frequency, spatial locality and orientation to make compensate to the variations of face instances occurred due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images produces Gabor face representations with high dimensional feature vectors. PCA and canonical covariate are then applied on the Gabor face representations to reduce the high dimensional feature spaces into low dimensional Gabor eigenfaces and Gabor canonical faces. Reduced eigenface vector and canonical face vector are fused together using weighted mean fusion rule. Finally, support vector machines (SVM) have trained with augmented fused set of features and perform the recognition task. The system has been evaluated with UMIST face database consisting of multiview faces. The experimental results demonstrate the efficiency and robustness of the proposed system for multi-view face images with high recognition rates. Complexity analysis of the proposed system is also presented at the end of the experimental results.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Robust multi-camera view face recognition does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Robust multi-camera view face recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Robust multi-camera view face recognition will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-81506

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.