Online human gesture recognition from motion data streams

Zhao, Xin, Li, Xue, Pang, Chaoyi, Zhu, Xiaofeng and Sheng, Quan Z. (2013). Online human gesture recognition from motion data streams. In: MM 2013 - Proceedings of the 2013 ACM Multimedia Conference. 21st ACM International Conference on Multimedia, MM 2013, Barcelona, Spain, (23-32). 21-25 October 2013. doi:10.1145/2502081.2502103

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Author Zhao, Xin
Li, Xue
Pang, Chaoyi
Zhu, Xiaofeng
Sheng, Quan Z.
Title of paper Online human gesture recognition from motion data streams
Conference name 21st ACM International Conference on Multimedia, MM 2013
Conference location Barcelona, Spain
Conference dates 21-25 October 2013
Proceedings title MM 2013 - Proceedings of the 2013 ACM Multimedia Conference
Journal name MM 2013 - Proceedings of the 2013 ACM Multimedia Conference
Place of Publication New York, NY, United States
Publisher ACM
Publication Year 2013
Sub-type Fully published paper
DOI 10.1145/2502081.2502103
Open Access Status
ISBN 9781450324045
Start page 23
End page 32
Total pages 10
Collection year 2014
Abstract/Summary Online human gesture recognition has a wide range of applications in computer vision, especially in human-computer interaction applications. Recent introduction of cost-effective depth cameras brings on a new trend of research on bodymovement gesture recognition. However, there are two major challenges: I) how to continuously recognize gestures from unsegmented streams, and ii) how to differentiate different styles of a same gesture from other types of gestures. In this paper, we solve these two problems with a new effective and efficient feature extraction method that uses a dynamic matching approach to construct a feature vector for each frame and improves sensitivity to the features of different gestures and decreases sensitivity to the features of gestures within the same class. Our comprehensive experiments on MSRC-12 Kinect Gesture and MSR-Action3D datasets have demonstrated a superior performance than the stat-of-the-art approaches. Copyright
Keyword Depth camera
Feature extraction
Gesture recognition
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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