A three-mode expressive feature model of action effort

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.

[1]  Demetri Terzopoulos,et al.  Multilinear Analysis of Image Ensembles: TensorFaces , 2002, ECCV.

[2]  L. Tucker,et al.  Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.

[3]  M. Alex O. Vasilescu.  Human motion signatures for character animation , 2001, SIGGRAPH 2001.

[4]  Ken-ichi Anjyo,et al.  Fourier principles for emotion-based human figure animation , 1995, SIGGRAPH.

[5]  James W. Davis,et al.  Expressive features for movement exaggeration , 2002, SIGGRAPH '02.

[6]  Joshua B. Tenenbaum,et al.  Separating Style and Content , 1996, NIPS.

[7]  Yuntao Cui,et al.  Learning-based hand sign recognition using SHOSLIF-M , 1995, Proceedings of IEEE International Conference on Computer Vision.

[8]  Allan D. Jepson,et al.  Priors, preferences and categorical percepts , 1996 .

[9]  David J. Fleet,et al.  Learning parameterized models of image motion , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[11]  Hiroshi Murase,et al.  Learning and recognition of 3D objects from appearance , 1993, [1993] Proceedings IEEE Workshop on Qualitative Vision.

[12]  Aaron Hertzmann,et al.  Style machines , 2000, SIGGRAPH 2000.

[13]  P. Kroonenberg,et al.  Individual differences and segment interactions in throwing , 1991 .

[14]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[15]  Aaron F. Bobick,et al.  Parametric Hidden Markov Models for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  J. Leeuw,et al.  Principal component analysis of three-mode data by means of alternating least squares algorithms , 1980 .

[17]  Rómer Rosales,et al.  Inferring body pose without tracking body parts , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[18]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[19]  S. Runeson,et al.  Visual perception of lifted weight. , 1981, Journal of experimental psychology. Human perception and performance.