The fundamental technical challenge of human face recognition is to deal with the extremely broad range of variations in a face's appearance due to pose, lighting, age, facial expression, distance and other factors. Ideal facial features should remain invariant under these variations. While current face recognition methods are limited in the conditions where they work, recent advances in the mathematical theory of invariants and recent connections forged with cryptology provide new insights for the face recognition problem that may help broaden the generality and robustness of face recognition systems. In this project, an interdisciplinary team will explore a unique approach that brings together the latest developments in the mathematics of integral invariants, psychophysical experiments on face recognition by humans, and state-of-the-art face recognition algorithms and system development. Specifically, we plan to address the following research goals: Establish a common mathematical foundation between cryptology and object recognition, in particular obtaining information-theoretical limits to data compression of human faces
Investigate the mathematical theory of integral invariants for 3D geometrical objects, and develop efficient invariant feature extraction and pattern recognition algorithms
Interact with a professional cartoonist and use experimental psychophysical evidence to assess perceptual significance and to explore biological interpretations of mathematical 3D integral invariant features in the context of human face recognition
Develop a prototype system implementation for 3D moving face recognition. In particular, we will focus on a scenario with multiple camera in a semi-controlled environment for access control and watch-list spotting applications
The approaches taken in this project are cutting-edge, unconventional, and promise significant breakthrough in advancing both the theory and practice of face recognition performance. Broad Impacts In this project we plan to hold a summer research experience program to serve under-represented groups; to develop a new biometric informatics class that involves undergraduate students in developing parts of prototype face recognition systems; to hold a man-machine face recognition contest to garner public awareness of this area and to attract young people to science and technology. Specifically, in both laboratories and courses we will foster an environment for students from both mathematics and computer science backgrounds to interact in learning and research, to stimulate new ideas and to appreciate the mutual impact and interactions between mathematics and computer science.
