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Proceedings Paper

Facial feature tracking by robust face segmentation and scalable rotational BMA
Author(s): Jung Sun Kim; Nam Ik Cho; Seok Cheol Kee; Sang Uk Lee
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Paper Abstract

We proposed an algorithm for the tracking of facial feature points based on the block matching algorithm (BMA) with a new shape of window considering the feature point characteristics and scale/angle changes of the face. The window used in the proposed algorithm is the set of pixels in the 8 radial lines of 0 degree(s),45 degree(s),... from the feature point, i.e. the window has the shape of cross plus 45 degree(s) rotated cross. This shape of window is shown to be more efficient than the conventional rectangular window in tracking the facial feature points, because the points and their neighbor are not usually the objects of rigid body. But since the feature points are usually on the edges of luminance or color changes, at least one of the radial line crosses the edge and it gives distinct measure for tracking the point. Also the radial line window requires less computational complexity than the rectangular window and more readily adjusted with respect to scale and angle changes. For the estimation of scale changes, the facial region is segmented at each frame using the normalized color, and the number of pixels in the facial region are compared.

Paper Details

Date Published: 4 January 2002
PDF: 7 pages
Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); doi: 10.1117/12.453025
Show Author Affiliations
Jung Sun Kim, Seoul National Univ. (South Korea)
Nam Ik Cho, Seoul National Univ. (South Korea)
Seok Cheol Kee, Samsung Advanced Institute of Technology (South Korea)
Sang Uk Lee, Seoul National Univ. (South Korea)


Published in SPIE Proceedings Vol. 4671:
Visual Communications and Image Processing 2002
C.-C. Jay Kuo, Editor(s)

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