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MIT Media Laboratory Perceptual Computing Section Technical Report 422
Also appears as MIT thesis for the degree of
Bachelor of Science in Electrical Engineering and Computer Science
Supervised by Alex P. Pentland

Eigenheads for Reconstruction

Kenneth B. Russell
Vision and Modeling Group
MIT Media Laboratory
20 Ames Street; Cambridge, MA 02139
kbrussel@media.mit.edu

Abstract

A framework is presented for recovering the 3D structure and visual appearance of a human head from sparse data obtained from a real-time tracking system. An eigenvector decomposition of CyberWare-scanned heads is used to code incoming information. Modular eigenspaces are used to decorrelate eigenfeatures (eyes, nose, and mouth) from the rest of the head data. We observe that the modular eigenspace encoding often does not perform as well as a single eigenspace, and offer reasons for this based on experimental evidence.

This work was supported in part by British Telecom and Texas Instruments.





Kenneth B Russell
Mon May 5 14:33:03 EDT 1997