Recognition and re-synthesis of 3D human motion with personalized variations

Author

Etemad, Seyed Ali ; Arya, Ali

Author_Institution

Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada

fYear

2009

fDate

2-4 April 2009

Firstpage

106

Lastpage

111

Abstract

This paper proposes a 3D view-invariant human action recognition method based on Hidden Markov Models. The natures of the actions, as well as the characteristics of the actors and different performance styles have been successfully recognized. The results have been compared to nearest neighbor and similarity search based recognition for further evaluation. Also the research addresses the problem of re-synthesis of motion. Transformation of moods, genders, and other characteristics of the actor have successfully been carried out, and the entire action has been re-synthesized for various purposes such as animation.

Keywords

computer animation; hidden Markov models; image motion analysis; image recognition; solid modelling; 3D human motion re-synthesis; 3D view-invariant human motion recognition; hidden Markov model; human action; nearest neighbor search; personalized animation; personalized variation; similarity search; Animation; Application software; Biological system modeling; Emotion recognition; Hidden Markov models; Humans; Interpolation; Military computing; Mood; Nearest neighbor searches; hidden Markov models; human action; recognition; style transformation; synthesis;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on

Conference_Location

Ouarzazate

Print_ISBN

978-1-4244-3756-6

Electronic_ISBN

978-1-4244-3757-3

Type

conf

DOI

10.1109/MMCS.2009.5256719

Filename

5256719