Face detection is the first step in human face
recognition and video surveillance. Fast and automatic detection of faces
from video sequences is an important task in security applications. The number,
location, size and orientation of human faces may vary from frame to frame.
A face detection and tracking algorithm from color images in the presence
of varying lighting conditions as well as complex background environment
is being developed in the VLSI Systems Laboratory. The goal of this research
work is to locate human faces in images in natural environments with unconstrained
lighting, varying face poses, and varying face geometries and skin colors.
The new method detects skin regions over the entire image, and then searches
for face candidates based on their spatial arrangements. Eye, mouth, and
face boundary maps constructed during the search process verify each face
candidate. A set of normalized parameters representing statistical and geometrical
features extracted from the segmented regions classifies them as face or
non-face regions based on a new classification strategy. It is envisaged
that the new method leads to successful detection of faces over a wide range
of facial variations in color, position, scale, rotation, pose, and expression.
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