Title
Real-Time Human Motion Capturing System
Abstract
This paper presents a real time vision-based human motion capturing and recognition system using two calibrated CCD cameras. We propose a simple but effective method to estimate the motion parameters (BAPs) of the human object by analyzing the vertical projection profile and the horizontal projection profile in each view to identify different arm and leg postures. With the identified postures, we can apply the Kalman filtering to capture the motion parameters (joint angels). Our method is divided into macro motion analysis and micro motion analysis. The former identifies certain well-defined postures and the latter traces the variation of joint angle or BAPs. In the experiments, we test 22 different arm and leg postures and show the errors of the estimated BAPs.
Year
DOI
Venue
2005
10.1109/ICIP.2005.1530307
2005 International Conference on Image Processing (ICIP), Vols 1-5
Keywords
Field
DocType
human tracking, motion parameter, kalman filtering, template matching, posture analysis
Computer vision,Recognition system,Vertical projection,Pattern recognition,Computer science,Human motion,Kalman filter,Artificial intelligence,Motion analysis,Motion estimation,Macro,Cognitive neuroscience of visual object recognition
Conference
ISSN
Citations 
PageRank 
1522-4880
1
0.37
References 
Authors
9
3
Name
Order
Citations
PageRank
Bau-cheng Shen1111.30
Huang-Chia Shih218721.98
Chung-lin Huang310.37