M. Comm. / Malicious acts such as fraud and terrorisms are continually becoming a more pressing threat. The need is growing daily for a cheap, non-intrusive technology, that does not make use of specialized equipment, which can identify individuals with or without their knowledge or permission, over the internet or in the public domain. The answer to this problem might be digital facial recognition, the authentication of a person according to the measurements and shape of his facial patterns (nodal points). Thus far the technology has primarily been used by law enforcement. The great strength of facial recognition is that it can scan multiple people in an area quickly, with or without their interaction with the system. The purpose of facial recognition surveillance is to implement it anywhere possible, for example shopping centres, street corners, hotel lobbies or train stations, and to be able to identify any individual finding himself in any of these areas. Also, if a larger system can be implemented, we would be able to track any individual wherever he goes. Through this, any suspicious character can be monitored and tracked if the need arises, ensuring that people can live in a much safer world.

by Leung Hoi-Chau. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 70-71). / Abstracts in English and Chinese. / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Previous Works --- p.2 / Chapter 2.1. --- Facial animations and facial surgery simulations / Chapter 2.2. --- Facial Action Coding System (FACS) / Chapter 2.3. --- The Boundary Element Method (BEM) in Computer Graphics / Chapter Chapter 3. --- The Facial Expression System --- p.7 / Chapter 3.1. --- Input to the system / Chapter 3.1.1. --- Orientation requirements for the input mesh / Chapter 3.1.2. --- Topology requirements for the input mesh / Chapter 3.1.3. --- Type of the polygons of the facial mesh / Chapter 3.2. --- Facial Modeling and Feature Recognition / Chapter 3.3. --- User Control / Chapter 3.4. --- Output of the system / Chapter Chapter 4. --- Boundary Element Method (BEM) --- p.12 / Chapter 4.1. --- Numerical integration of the kernels / Chapter 4.1.1. --- P and Q are different / Chapter 4.1.2. --- P and Q are identical / Chapter 4.1.2.1. --- Evaluation of the Singular Traction Kernel / Chapter 4.1.2.2. --- Evaluation of the Singular Displacement Kernel / Chapter 4.2. --- Assemble the stiffness matrix / Chapter Chapter 5. --- Facial Modeling --- p.18 / Chapter 5.1. --- Offset of facial mesh / Chapter 5.2. --- Thickening of Face Contour / Chapter Chapter 6. --- Facial Feature Recognition --- p.22 / Chapter 6.1. --- Extract all contour edges from the facial mesh / Chapter 6.2. --- Separate different holes from the contour edges / Chapter 6.3. --- Locating the bounding boxes of different holes / Chapter 6.4. --- Determine the facial features / Chapter 6.4.1. --- Eye positions / Chapter 6.4.2. --- Mouth position and Face / Chapter 6.4.3. --- Nose position / Chapter 6.4.4. --- Skull position / Chapter Chapter 7. --- Boundary Conditions in the system --- p.28 / Chapter 7.1. --- Facial Muscles / Chapter 7.2. --- Skull Bone / Chapter 7.3. --- Facial Muscle recognition / Chapter 7.3.1. --- Locating muscle-definers / Chapter 7.3.2. --- Locating muscles / Chapter 7.4. --- Skull Bone Recognition / Chapter 7.5. --- Refine the bounding regions of the facial features / Chapter 7.6. --- Add/Remove facial muscles / Chapter Chapter 8. --- Muscles Movement --- p.40 / Chapter 8.1. --- Muscle contraction / Chapter 8.2. --- Muscle relaxation / Chapter 8.3. --- The Muscle sliders / Chapter Chapter 9. --- Pre-computation --- p.44 / Chapter 9.1. --- Changing the Boundary Values / Chapter Chapter 10 --- . Implementation --- p.46 / Chapter 10.1. --- Data Structure for the facial mesh / Chapter 10.2. --- Implementation of the BEM engine / Chapter 10.3. --- Facial modeling and the facial recognition / Chapter Chapter 11 --- . Results --- p.48 / Chapter 11.1. --- Example 1 (low polygon man face) / Chapter 11.2. --- Example 2 (girl face) / Chapter 11.3. --- Example 3 (man face) / Chapter 11.4. --- System evaluation / Chapter Chapter 12 --- . Conclusions --- p.67 / References --- p.70