Title :
A three-mode expressive feature model of action effort
Author :
Davis, James W. ; Gao, Hui ; Kannappan, Vignesh S.
Author_Institution :
Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA
Abstract :
We present an expressive feature model for recognizing the performance effort of human actions. A set of low and high effort examples for an action are initially factored into its three-mode principal components, followed by a learning phase to compute the expressive features required to bring the model estimation of effort into agreement with perceptual judgements. The approach is demonstrated using real and illusory movements.
Keywords :
computer vision; gait analysis; image motion analysis; learning (artificial intelligence); parameter estimation; principal component analysis; video signal processing; athletic training; computer vision; ergonomic monitoring system; expressive feature model; human action effort estimation; learning phase; motion-capture animations; perceptual dynamics; surveillance systems; three-mode principal components; video annotation; Animation; Computational intelligence; Hidden Markov models; Humans; Information science; Injuries; Legged locomotion; Packaging; Patient monitoring; Phase estimation;
Conference_Titel :
Motion and Video Computing, 2002. Proceedings. Workshop on
Print_ISBN :
0-7695-1860-5
DOI :
10.1109/MOTION.2002.1182226
