3-D human posture recognition system using 2-D shape features

Jwu-Sheng Hu*, Tzung Min Su, Pei Ching Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper presents an integrated framework for recognizing 3D human posture from 2D images. A flexible combinational algorithm motivated by the novel view expressed by Cyr and Kimia [1] is proposed to generate the aspects of 3D human postures as the posture prototype using features extracted from the collected 2D images sampled at random intervals from the viewing sphere. Frequency and phase information of the posture are calculated from the Fourier descriptors (FDs) of the sampled points on the posture contour as the main and assistant features to extract the characteristic views as the aspects. Moreover, a modified particle filter is applied to improve the robustness of human posture recognition for continuous monitoring. Experimental trials on synthetic and real sequences have shown the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Robotics and Automation, ICRA'07
Pages3933-3938
Number of pages6
DOIs
StatePublished - 27 Nov 2007
Event2007 IEEE International Conference on Robotics and Automation, ICRA'07 - Rome, Italy
Duration: 10 Apr 200714 Apr 2007

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2007 IEEE International Conference on Robotics and Automation, ICRA'07
CountryItaly
CityRome
Period10/04/0714/04/07

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