Hand gesture recognition using 8-directional vector chains in quantization space

Seongjo Lee, Sohyun Sim, Kyhyun Um, Young Sik Jeong, Kyungeun Cho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationUbiquitous Computing Application and Wireless Sensor, UCAWSN-2014
EditorsYi Pan, Gangman Yi, Han-Chieh Chao, James J. Park
PublisherSpringer Verlag
Pages333-340
Number of pages8
ISBN (Electronic)9789401796170
DOIs
StatePublished - 2015
Event2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network, UCAWSN 2014 - , Korea, Republic of
Duration: 7 Jul 201410 Jul 2014

Publication series

NameLecture Notes in Electrical Engineering
Volume331
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network, UCAWSN 2014
Country/TerritoryKorea, Republic of
Period7/07/1410/07/14

Keywords

  • Hand gesture recognition
  • Hidden Markov model
  • Kinect sensor
  • Multimedia content

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