1. By Paige Querry

2. ● Who uses Face Recognition ● Basics ● Methods ● Pros and Cons of Methods ● Stats ● Areas of Research ● Conclusion Overview

3. ● London Borough of Newham, UK ● German Federal Police  Frankfurt Rhein-Main Airport ● US Department of State ● Super Bowl XXXV 2001, Tampa Bay FL ● Facebook ● PA Justice Network ● Mexican Government  2000 Presidential Election ● Most covert and not publicized Who uses Face Recognition

4. ● Security at ATM’s ● Unlocking Mobile Devices  Android’s Visidon Applock ● Password Replacement ● Digital Photography ● Attendance Monitoring New and Potential Uses

5. ● Geometric  Defines distinguishing features  Points and vectors  Not widely used ● Photometric  Statistical approach move images to values  Common Coordinate System Cloud point storage Widely used  Intrinsic Coordinate System Template point storage Basics

6. ● Photometric ● Stores facial images in cloud of data points ● Compares 2 clouds  Rotates and adjusts clouds for best match  Uses distances between points for verification ● Interactive Closest Point (IPC) ● Store cloud for each face ● 600kB for 50,000 point cloud ● Some algorithms 99% accuracy Methods Common Coordinate System

7. ● Photometric ● Stores facial images as coordinates on a template ● Uses tip of nose and slant of bridge  Limited variation in nose area  Lack of facial muscles at nose area ● Less error with facial expressions ● 94.6% accuracy Methods Intrinsic Coordinate System

8. ● How it works  Determine the region for the face  Determine vertical symmetry plane  Determine nose tip and nose slope  Transform point cloud to coordinate system  Construct range image Methods Intrinsic Coordinate System

9. ● How it works – Overlapping regions  Minimizes errors due to facial expressions  Minimize addition of glasses  Minimize occlusion by hair ● Hole filling and spike removal  Holes/blanks due to scanner failure  Filled in by interpolation Methods Intrinsic Coordinate System

10. ● Some of the Math  Small hole filling Uses interpolation  Large hole filling Uses the symmetry of the face r(i,j)= distance between pixels i and j  Likelihood Ratio Classifier p(x|c) is the conditional probability on a feature vector x m is the dimension of the feature vector. μT and μc are the mean feature vectors Methods Intrinsic Coordinate System

11. ● Common Coordinate System Pros:Cons: Excellent Accuracy Slow Can store image Requires lots of storage ● Intrinsic Coordinate System Pros:Cons: High Accuracy Method incomplete Fast Pros and Cons of Methods

12. Stats Top performing 3D face recognition methods Verification rate VR @ FAR = 0.1% Method Mask I Mask II Mask III All vs all Common Coordinate System Maurer et al. (2005) 86.5% Kakadiaris et al. (2007) 97.2% 97.1% 97.0% Faltemier et al. (2008a) 94.8% 93.2% Alyüz et al. (2009) 85.8% 86.0% 86.1% Al-Osaimi et al. (2009) 94.6% 94.1% 94.1% Queirolo et al. (2010) 96.6% 96.5% Intrinsic Coordinate System Spreeuwers 94.6% 94.6% 94.6% 94.6%

13. Areas of Research ● Weighting the regions ● Adaptations for exaggerated facial expressions ● Advanced hole filling ● Refine nose tip location ● Testing with partial facial occlusion  Hair  Glasses  Hats

14. Conclusions ● Compilation of a variety of methods ● Image post processing improves performance ● One time face registration ● Compensates for facial expressions ● Lower storage requirements ● Faster registration

15. References Spreeuwers, Luuk. (2011). Fast and Accurate 3D Face Recognition. International Journal Compute Vision, 93, 389 - 414. Tang, X. Chen, J. and Moon, Y. (2008). Accurate 3D face registration based on the symmetry plane analysis on nose regions. In Proceedings of the 16 th European signal processing conference (EU SIPCO 2008), Lausanne, Switzerland. Wikipedia. (2013). Facial recognition system. Retreived on 2/18/13 from http://en.wikipedia.org/wiki/Face_recognition Starovoitov, V. Samal, D. Briliuk, D. (2002). Three Approaches for Face Recognition. The 6 th International Conference on Pattern Recognition and image analysis, October 21-26, 2002, 707-711.

16. Questions