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\Large

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{\Huge The Department of Computer Science\\ 
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University of Nevada, Reno}

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{\Large cordially invites you to a Master's colloquium}

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        {\Huge \bf Robust 3D Head Pose Classification \\
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	Using Wavelets}

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        A thesis submitted in partial fulfillment of the\\
        requirements for the degree of Master of Science\\
        with a major in Computer Engineering.

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        by

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        {\huge Mukesh C. Motwani}

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\noindent
        {\bf Abstract:} This thesis describes a robust method for 
estimating face pose from a video sequence featuring views of a 
human head under variable lighting and facial expression conditions. 
Wavelet transform is used to decompose the image into multi-resolution 
face images containing both spatial and spatial-frequency information.
Principal component analysis (PCA) is used to project a
mid-frequency, low-resolution sub-band face pose onto a pose
eigen-space where the first three eigen coefficients are most
sensitive to pose and follow a trajectory as the pose changes. Any
unknown pose can then be estimated finding the Euclidean distance
of the first three eigen coefficients of the query image from the
estimated trajectory. Wavelet transform reduces the computational
load on the PCA and makes the algorithm robust against
illumination changes and facial expression. An efficiency of 84\%
was observed for test images under different environment
conditions not included during training.



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\Huge
{\bf 1:15 pm, Thursday, December 5, 2002}
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{\bf Room 344, Scrugham Engineering and Mines}

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{\Large 
for more information contact 
Dr. Fred Harris @ 784-6571 (fredh@cs.unr.edu)
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