One shot learning gesture recognition with Kinect sensor

Wu, Di, Zhu, Fan, Shao, Ling and Zhang, Hui (2012) One shot learning gesture recognition with Kinect sensor. In: Proceedings of the 20th ACM international conference on Multimedia. Association for Computing Machinery (ACM), JPN, pp. 1303-1304. ISBN 978-1-4503-1089-5

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Abstract

Gestures are both natural and intuitive for Human-Computer-Interaction (HCI) and the one-shot learning scenario is one of the real world situations in terms of gesture recognition problems. In this demo, we present a hand gesture recognition system using the Kinect sensor, which addresses the problem of one-shot learning gesture recognition with a user-defined training and testing system. Such a system can behave like a remote control where the user can allocate a specific function using a prefered gesture by performing it only once. To adopt the gesture recognition framework, the system first automatically segments an action sequence into atomic tokens, and then adopts the Extended-Motion-History-Image (Extended-MHI) for motion feature representation. We evaluate the performance of our system quantitatively in Chalearn Gesture Challenge, and apply it to a virtual one shot learning gesture recognition system.

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: Pure Connector
Date Deposited: 16 Feb 2017 02:26
Last Modified: 22 Apr 2020 11:07
URI: https://ueaeprints.uea.ac.uk/id/eprint/62636
DOI: 10.1145/2393347.2396454

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