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http://dx.doi.org/10.6109/jkiice.2018.22.3.471

AdaBoost-based Gesture Recognition Using Time Interval Window Applied Global and Local Feature Vectors with Mono Camera  

Hwang, Seung-Jun (Department of Electronics and Information Engineering, Korea Aerospace University)
Ko, Ha-Yoon (Department of Electronics and Information Engineering, Korea Aerospace University)
Baek, Joong-Hwan (Department of Electronics and Information Engineering, Korea Aerospace University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.22, no.3, 2018 , pp. 471-479 More about this Journal
Abstract
Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.
Keywords
3D Gesture Recognition; Pattern Recognition; Machine Learning; AdaBoost; Body Segmentation;
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Times Cited By KSCI : 2  (Citation Analysis)
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