Fast face localization and verification J.Matas, K.Johnson,J.Kittler

1. Fast face localization and verificationJ.Matas, K.Johnson,J.Kittler Presented by: Dong Xie

2. Introduction • Personal identification (authentication, verification of identity) – security applications. • Identification vs. Recognition • Small number of reference images vs. larger database • Near real-time vs. w/o time constraint • Previously unseen person vs. image from training database

3. In this article… • They propose an identification method based on optimized robust correlation. • An integrated approach: localization, normalization as well as identification is achieved simultaneously. • To that end, a robust form of correlation is evaluated inside an optimization loop. • Random sampling to speed up evaluation of the cost function inside the optimization loop.

4. Optimized robust correlation… • Objective: find the global extremum in a multi-dimensional search space that corresponds to the best match between a pair of images • Score function: A combined score function. • Optimization method: • Each iteration, the transformation between reference and test image is perturbed by adding a random vector drawn from an exponential distribution • New transformation is accepted only if score was increased. • Random sampling

5. M2VTS Multi-modal Database: 5 ‘shots’/person over a period of several weeks

6. Example of output 3a-d Successful Se-h Failed

7. High Score imposter test

8. Performance of the optimized robust correlation • Equal Error Rate(EER): (a)search method.(b)number of test images used • Near Real time (0.24s/single identification): • (c) search method(client test) (d) client and imposter.

9. EER for Optimized Robust Correlation(6b): 4.8% - single, randomly chosen 3.1% - sequence of test images

10. Conclusion… • A fast face localization and verification based on a robust form of correlation. • Optimization: random sampling speed the evaluation of correlation 25 times real time. • Recognition: Optimized Robust Correlation outperformed the two standard techniques.

11. Questions?