Feature-Strengthened Gesture Recognition Model Based on Dynamic Time Warping For Multi-Users


KIPS Transactions on Software and Data Engineering, Vol. 5, No. 10, pp. 503-510, Oct. 2016
10.3745/KTSDE.2016.5.10.503,   PDF Download:
Keywords: Gesture Recognition, Machine Learning
Abstract

FsGr model, which has been proposed recently, is an approach of accelerometer-based gesture recognition by applying DTW algorithm in two steps, which improved recognition success rate. In FsGr model, sets of similar gestures will be produced through training phase, in order to define the notion of a set of similar gestures. At the 1st attempt of gesture recognition, if the result turns out to belong to a set of similar gestures, it makes the 2nd recognition attempt to feature-strengthened parts extracted from the set of similar gestures. However, since a same gesture show drastically different characteristics according to physical traits such as body size, age, and sex, FsGr model may not be good enough to apply to multi-user environments. In this paper, we propose FsGrM model that extends FsGr model for multi-user environment and present a program which controls channel and volume of smart TV using FsGrM model.


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Cite this article
[IEEE Style]
S. K. Lee, H. M. Um, H. T. Kwon, "Feature-Strengthened Gesture Recognition Model Based on Dynamic Time Warping For Multi-Users," KIPS Transactions on Software and Data Engineering, vol. 5, no. 10, pp. 503-510, 2016. DOI: 10.3745/KTSDE.2016.5.10.503.

[ACM Style]
Suk Kyoon Lee, Hyun Min Um, and Hyuck Tae Kwon. 2016. Feature-Strengthened Gesture Recognition Model Based on Dynamic Time Warping For Multi-Users. KIPS Transactions on Software and Data Engineering, 5, 10, (2016), 503-510. DOI: 10.3745/KTSDE.2016.5.10.503.