Journal
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
Volume 24, Issue 11, Pages 1935-1944Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSVT.2014.2302538
Keywords
Hand gesture recognition; human-computer interaction (HCI); RGB-D sensor
Categories
Funding
- National Science Foundation CNS [1314484]
- Office of Naval Research [N00014-12-1-1028]
- U.S. Army Research Office [W911NF-13-1-0160]
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1314484] Funding Source: National Science Foundation
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In RGB-D sensor-based pose estimation, training data collection is often a challenging task. In this paper, we propose a new hand motion capture procedure for establishing the real gesture data set. A 14-patch hand partition scheme is designed for color-based semiautomatic labeling. This method is integrated into a vision-based hand gesture recognition framework for developing desktop applications. We use the Kinect sensor to achieve more reliable and accurate tracking under unconstrained conditions. Moreover, a hand contour model is proposed to simplify the gesture matching process, which can reduce the computational complexity of gesture matching. This framework allows tracking hand gestures in 3-D space and matching gestures with simple contour model, and thus supports complex real-time interactions. The experimental evaluations and a real-world demo of hand gesture interaction demonstrate the effectiveness of this framework.
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