Title
A real-time model-based human motion tracking and analysis for human computer interface systems
Abstract
This paper introduces a real-time model-based human motion tracking and analysis method for human computer interface (HCI). This method tracks and analyzes the human motion from two orthogonal views without using any markers. The motion parameters are estimated by pattern matching between the extracted human silhouette and the human model. First, the human silhouette is extracted and then the body definition parameters (BDPs) can be obtained. Second, the body animation parameters (BAPs) are estimated by a hierarchical tritree overlapping searching algorithm. To verify the performance of our method, we demonstrate different human posture sequences and use hidden Markov model (HMM) for posture recognition testing.
Year
DOI
Venue
2004
10.1155/S1110865704401206
EURASIP J. Adv. Sig. Proc.
Keywords
Field
DocType
markov model,method track,human motion,motion parameter,human silhouette,human model,human computer interface system,analysis method,real-time model-based human motion,different human posture sequence,human computer interface,human computer interaction,image recognition,hidden markov models,motion estimation,real time
Real time model,Computer vision,Search algorithm,Silhouette,Computer science,Human motion,Human–computer interaction,Artificial intelligence,Animation,Motion estimation,Hidden Markov model,Pattern matching
Journal
Volume
Issue
ISSN
2004,
11
1687-6180
Citations 
PageRank 
References 
4
0.64
17
Authors
2
Name
Order
Citations
PageRank
Chung-Lin Huang154037.61
Chia-Ying Chung251.02