Extraction and classification of visual motion patterns for handgesture recognition
Ming-Hsuan Yang
Ahuja, N.
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL;
This paper appears in: Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on
Publication Date: 23-25 Jun 1998
On page(s): 892-897
Meeting Date: 06/23/1998 - 06/25/1998
Location: Santa Barbara, CA, USA
ISSN: 1063-6919
ISBN: 0-8186-8497-6
References Cited: 12
INSPEC Accession Number: 5985944
Digital Object Identifier: 10.1109/CVPR.1998.698710
Current Version Published: 2002-08-06
Abstract
We present a new method for extracting and classifying motion
patterns to recognize hand gestures. First, motion segmentation of the
image sequence is generated based on a multiscale transform and
attributed graph matching of regions across frames. This produces region
correspondences and their affine transformations. Second, color
information of motion regions is used to determine skin regions. Third,
human head and palm regions are identified based on the shape and size
of skin areas in motion. Finally, affine transformations defining a
region's motion between successive frames are concatenated to construct
the region's motion trajectory. Gestural motion trajectories are then
classified by a time-delay neural network trained with backpropagation
learning algorithm. Our experimental results show that hand gestures can
be recognized well using motion patterns
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