Face Verification using Correlation Filters

Face verification is an important tool for authentication of an individual and it can be of significant value in security and e-commerce applications. This paper deals with the application of correlation filters [1] for face verification. The performance of a specific type of correlation filter called the minimum average correlation energy (MACE) filter [2] is evaluated using a facial expression database collected at the Advanced Multimedia Processing Lab at Carnegie Mellon University (CMU). A comparison of verification performance between the correlation filter method and Individual Eigenface Subspace Method (IESM) is also presented. It is seen that these correlation filters offer significant potential for face verification.

[1]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[2]  D Casasent,et al.  Multivariant technique for multiclass pattern recognition. , 1980, Applied optics.

[3]  B. V. K. Vijaya Kumar,et al.  Efficient Calculation of Primary Images from a Set of Images , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  D. Casasent,et al.  Minimum average correlation energy filters. , 1987, Applied optics.

[5]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[6]  B V Kumar,et al.  Tutorial survey of composite filter designs for optical correlators. , 1992, Applied optics.

[7]  Abhijit Mahalanobis,et al.  Evaluation of MACH and DCCF correlation filters for SAR ATR using the MSTAR public database , 1998, Defense, Security, and Sensing.

[8]  Tsuhan Chen,et al.  Tracking of multiple faces for human-computer interfaces and virtual environments , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[9]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression (PIE) database , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[10]  B. V. K. Vijaya Kumar,et al.  Face authentication for multiple subjects using eigenflow , 2003, Pattern Recognit..