Gesture recognition using Bezier curves for visualization navigation from registered 3-D data
This paper presents a gesture recognition system for visualization navigation. Scientists are interested in developing interactive settings for exploring large data sets in an intuitive environment. The input consists of registered 3-D data. A geometric method using Bezier curves is used for the trajectory analysis and classification of gestures. The hand gesture speed is incorporated into the algorithm to enable correct recognition from trajectories with variations in hand speed. The method is robust and reliable: correct hand identification rate is 99.9% (from 1641 frames), modes of hand movements are correct 95.6% of the time, recognition rate (given the right mode) is 97.9%. An application to gesture-controlled visualization of 3D bioinformatics data is also presented. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
bezier curves visualization navigation gesture recognition system motion analysis hand tracking human-computer interaction region detection and identification 3-d trajectory analysis