Publication: Gesture Recognition for Traffic Hand-Signals Training Simulator Using Kinect
Issued Date
2019-02-22
Resource Type
ISSN
21593450
21593442
21593442
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2-s2.0-85063219004
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Mahidol University
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SCOPUS
Bibliographic Citation
IEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol.2018-October, (2019), 297-302
Suggested Citation
Atid Puwatnuttasit, Worapan Kusakunniran Gesture Recognition for Traffic Hand-Signals Training Simulator Using Kinect. IEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol.2018-October, (2019), 297-302. doi:10.1109/TENCON.2018.8650201 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/50644
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Title
Gesture Recognition for Traffic Hand-Signals Training Simulator Using Kinect
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Abstract
© 2018 IEEE. Human gesture recognition is a way to interpret human movement and/or posture automatically. In this paper, it is used as the main interaction for the developed traffic hand-signals training simulator, based on the Kinect skeleton tracking system. Therefore, the gestures defined in this work are traffic hand-signals used in Thailand. They consist of both static postures and dynamic movements. The recognition is trained and constructed using the rule-based system. The rules must be trained to distinguish these traffic hand-signals, based on both movement information and depth-map information of hands. Then, in a part of the simulator, the artificial intelligent techniques are applied to make it realistic and challenge. The techniques include finite state machine, pathfinding, and path following. They are implemented and used for individual vehicles in the scene. Then, the performances of these two key components of the developed system, the hand-signals recognition and the traffic simulator, are evaluated. It is shown that the system can achieve a very promising performance in both aspects of the recognition accuracy and the user satisfaction.
