Hand Gesture Recognition Using 8-Directional Vector Chains in Quantization Space
- Authors
- Lee, Seongjo; Sim, Sohyun; Um, Kyhyun; Jeong, Young-Sik; Cho, Kyungeun
- Issue Date
- 2015
- Publisher
- SPRINGER
- Keywords
- Hand gesture recognition; Kinect sensor; Hidden Markov model; Multimedia content
- Citation
- UBIQUITOUS COMPUTING APPLICATION AND WIRELESS SENSOR, v.331, pp 333 - 340
- Pages
- 8
- Indexed
- SCOPUS
- Journal Title
- UBIQUITOUS COMPUTING APPLICATION AND WIRELESS SENSOR
- Volume
- 331
- Start Page
- 333
- End Page
- 340
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/25361
- DOI
- 10.1007/978-94-017-9618-7_31
- ISSN
- 1876-1100
1876-1119
- Abstract
- This paper proposes a hand gesture recognition technique that allows users to enjoy uninterrupted interaction with a variety of multimedia applications. Hand gestures are recognized using joint information acquired from a Kinect sensor, and the recognized gestures are applied to multimedia content. To this end, hand gestures are quantized in the grid space, expressed using an 8-directional vector chain, and finally recognized on the basis of a hidden Markov model. To assess the proposed approach, we define the hand gestures used in the "Smart Interior" multimedia application, and collect a dataset of gestures using the Kinect. Our experiments demonstrate a high recognition ratio of between 90 and 100 %. Furthermore, the experiments identify the possibility of applying this approach to a variety of multimedia content by verifying its superior operation in actual applications.
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Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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