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http://dx.doi.org/10.5909/JBE.2012.17.3.447

Hand Gesture Recognition from Kinect Sensor Data  

Cho, Sun-Young (Dept. of Computer Science, Yonsei University)
Byun, Hye-Ran (Dept. of Computer Science, Yonsei University)
Lee, Hee-Kyung (Broadcasting & Telecommunications Convergence Media Research Dept., ETRI)
Cha, Ji-Hun (Broadcasting & Telecommunications Convergence Media Research Dept., ETRI)
Publication Information
Journal of Broadcast Engineering / v.17, no.3, 2012 , pp. 447-458 More about this Journal
Abstract
We present a method to recognize hand gestures using skeletal joint data obtained from Microsoft's Kinect sensor. We propose a combination feature of multi-angle histograms robust to orientation variations to represent the observation sequence of skeletons. The proposed feature efficiently represents the orientation variations of gestures that can be occurred according to person or environment by combining the multiple angle histograms with various angular-quantization levels. The gesture represented as combination of multi-angle histograms and random decision forest classifier improve the recognition performance. We conduct the experiments in hand gesture dataset obtained from a kinect sensor and show that our method outperforms the other methods by comparing the recognition performance.
Keywords
Hand gesture recognition; Combination of multi-angle histograms; Kinect;
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