Face Detection and Modeling for Recognition - Biometrics Research ...

verify the face present in an image in the recognition stage.
This thesis has developed
a robust face detection module which is used to facilitate applications such as face
tracking for surveillance, and face modeling for identification (as well as verification).
We will briefly discuss the topics of face detection and recognition, face modeling as
well as compression, and face-based image retrieval in the following sections.
1.4 Face Detection and Recognition
Human activity is a major concern in a wide variety of applications such as video
surveillance, human computer interface, face recognition [37], [36], [38], and face
image database management [40]. Detecting faces is a crucial step and usually the
first one in these identification applications.
However, due to various head poses,
illumination conditions, occlusion, and distances between teh sensor and the subject
(which may result in a blurred face), detecting human faces is an extremely difficult
task under unconstrained environments (see images in Figs. 1.13 (a) and (b)). Most
face recognition algorithms assume that the problem of face detection has been solved,
that is, the face location is known. Similarly, face tracking algorithms (e.g., [61])
often assume the initial face location is known. Since face detection can be viewed
as a two-class (face vs. non-face) classification problem, some techniques developed
for face recognition (e.g., holistic/template approaches [21], [62], [63], [64], featurebased
approaches [65], and their combination [66]) have been used to detect faces.
However, these detection techniques are computationally very demanding and cannot
handle large variations in faces. In addition to the face location, a face detection
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