Fuzzy qualitative human motion analysis

Chan, C.S. and Liu, H.H. (2009) Fuzzy qualitative human motion analysis. IEEE Transactions on Fuzzy Systems, 17 (4). pp. 851-862. ISSN 1063-6706,

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This paper proposes a fuzzy qualitative approach to vision-based human motion analysis with an emphasis on human motion recognition. It achieves feasible computational cost for human motion recognition by combining fuzzy qualitative robot kinematics with human motion tracking and recognition algorithms. First, a data-quantization process is proposed to relax the computational complexity suffered from visual tracking algorithms. Second, a novel human motion representation, i.e., qualitative normalized template, is developed in terms of the fuzzy qualitative robot kinematics framework to effectively represent human motion. The human skeleton is modeled as a complex kinematic chain, and its motion is represented by a series of such models in terms of time. Finally, experiment results are provided to demonstrate the effectiveness of the proposed method. An empirical comparison with conventional hidden Markov model (HMM) and fuzzy HMM (FHMM) shows that the proposed approach consistently outperforms both HMMs in human motion recognition.

Item Type: Article
Additional Information: Chan, Chee Seng Liu, Honghai
Uncontrolled Keywords: computational complexity , data-quantization process , fuzzy HMM , fuzzy qualitative human motion analysis , fuzzy Motion recognition , human motion tracking , vision-based human motion analysis , visual tracking algorithms
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science & Information Technology > Department of Artificial Intelligence
Depositing User: Miss Nur Jannatul Adnin Ahmad Shafawi
Date Deposited: 15 Apr 2013 01:51
Last Modified: 08 Jul 2017 03:57
URI: http://eprints.um.edu.my/id/eprint/5553

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