IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exemplar-Based Face Recognition from Video
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
An Evaluation of Multimodal 2D+3D Face Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Optimal Pose for Face Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Face recognition from a single image per person: A survey
Pattern Recognition
Multi-frame Approaches To Improve Face Recognition
WMVC '07 Proceedings of the IEEE Workshop on Motion and Video Computing
A weighted probabilistic approach to face recognition from multiple images and video sequences
Image and Vision Computing
FRVT 2006 and ICE 2006 Large-Scale Experimental Results
IEEE Transactions on Pattern Analysis and Machine Intelligence
From still image to video-based face recognition: an experimental analysis
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A competitive model for semi-supervised discriminant analysis
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
| Hi-index | 0.01 |
In order to handle complex face image variations in face recognition, multi-image face recognition has been proposed, instead of using a single still-image-based approach. In many practical scenarios, multiple images can be easily obtained in enrollment and query stages, for example, using video. By assessing these images, a good ''quality'' image(s) will be selected for recognition using conventional still-image-based recognition algorithms so that the recognition performance can be improved. However, existing methods do not fully utilize all images information. In this paper, two new measurements, namely discriminability index (DI) and reliability index (RI), are proposed to evaluate the enrolled and query images, respectively. By considering the distribution of enrolled images from individuals, the discriminability index of each image is calculated and a weight is assigned. For testing images, a reliability index is calculated based on matching quality between the testing images and enrolled images. If the reliability index of a testing image is small, the testing image will be discarded as it may degrade the recognition performance. To evaluate and demonstrate the use of DI and RI, we adopt the combining classifier method with eigenface representations in input and kernel feature spaces. CMU-PIE, YaleB and FRGC V2.0 databases are used for experiments. Experimental results show that the recognition performance, with three popular combination rules, can be increased by more than 10% on average using DI and RI.