Examplers based image fusion features for face recognition

Details Examplers based image fusion features for face recognition Examplers based image fusion features for face recognition

2012-01-28

arxiv.org/abs/1201.5947v1

Computer Science

Computer Vision and Pattern Recognition

Scientific paper

Examplers of a face are formed from multiple gallery images of a person and are used in the process of classification of a test image. We incorporate such examplers in forming a biologically inspired local binary decisions on similarity based face recognition method. As opposed to single model approaches such as face averages the exampler based approach results in higher recognition accu- racies and stability. Using multiple training samples per person, the method shows the following recognition accuracies: 99.0% on AR, 99.5% on FERET, 99.5% on ORL, 99.3% on EYALE, 100.0% on YALE and 100.0% on CALTECH face databases. In addition to face recognition, the method also detects the natural variability in the face images which can find application in automatic tagging of face images.

Affiliated with

Also associated with

No associations

Rating

Examplers based image fusion features for 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 Examplers based image fusion features for face recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Examplers based image fusion features for face recognition will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-257452