By Topic

Human Behavior Analysis Using Deformable Triangulations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Yung-Tai Hsu ; Dept. of Electr. Eng., Yuan-Ze Univ., Chung-li ; Hsieh, Jun-Wei ; Hai-Feng Kao ; Liao, H.-Y.M.

This paper presents a new posture classification system to analyze different human behaviors directly from video sequences using the technique of triangulation. For well analyzing each posture in the video sequences, we propose a triangulation-based method to triangulate it to different triangle meshes from which two important posture features are then extracted, i.e., the ones of skeleton and centroid context. The first one is used for a coarse search and the second one is for a finer classification to classify postures in more details. For the first descriptor, we take advantages of a dfs (depth-first search) scheme to extract the skeleton features of a posture from its triangulation result. Then, with the help of skeleton information, we can define a new shape descriptor, i.e., centroid context, to describe a posture up to a semantic level. That is, the centroid context is a finer descriptor to describe a posture not only from its whole shape but also from its body parts. Since the two descriptors are complement to each other, all desired human postures can be compared and classified very accurately. The nice ability of posture classification can help us generate a set of key postures for transferring a behavior sequence to a set of symbols. Then, a novel string matching scheme is proposed to analyze different human behaviors. Experimental results have proved that the proposed method is robust, accurate, and powerful in human behavior analysis

Published in:

Multimedia Signal Processing, 2005 IEEE 7th Workshop on

Date of Conference:

Oct. 30 2005-Nov. 2 2005