2026-09-19T20:49:34Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/81290 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Huang, Thomas S. Colmenarez, Antonio Jose 2015-09-25T20:10:24Z 2015-09-25T20:10:24Z 10000-01-01 1999 1999 The algorithm described in this thesis for embedded face and facial expression recognition is based on a novel probabilistic framework. In this novel framework, faces are modeled not only by their appearance, but also by the spatio-temporal deformation pattern of their expressions. Face recognition and facial expression recognition are carried out in a maximum likelihood setup. Given an image sequence, the algorithm finds the person's model and the facial expression that maximizes the likelihood probability of the observed images. In this framework, facial appearance matching is enhanced by facial expression modeling. Also, changes in facial features due to expressions are used together with facial deformation patterns to perform expression recognition. Made available in DSpace on 2015-09-25T20:10:24Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 9944823.pdf: 4240818 bytes, checksum: 208dcebc9919fe43f395117e61d0650d (MD5) Previous issue date: 1999 Embargo set by: Seth Robbins for item 82571 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 88 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999. http://hdl.handle.net/2142/81290 (MiAaPQ)AAI9944823 eng Computer Science Facial Analysis From Continuous Video With Application to Human -Computer Interface text Electrical Engineering Electrical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.