NDLI: Hand pose recognition using curvature scale space

Content Provider	IEEE Xplore Digital Library
Author	Chin-Chen Chang I-Yen Chen Yea-Shuan Huang
Copyright Year	2002
Description	Author affiliation: Comput. & Commun. Res. Labs., Ind. Technol. Res. Inst., Hsinchu, Taiwan (Chin-Chen Chang; I-Yen Chen; Yea-Shuan Huang)
Abstract	We present a feature extraction approach based on curvature scale space (CSS) for translation, scale, and rotation invariant recognition of hand poses. First, the CSS images are used to represent the shapes of boundary contours of hand poses. Then, we extract the multiple sets of CSS features to overcome the problem of deep concavities in contours of hand poses. Finally, nearest neighbour techniques are used to perform CSS matching between the multiple sets of input CSS features and the stored CSS features for hand pose identification. Results show the proposed approach can extract the multiple sets of CSS features from the input images and perform well for recognition of hand poses.
Starting Page	386
Ending Page	389
File Size	244325
Page Count	4
File Format	PDF
ISBN	076951695X
ISSN	10514651
DOI	10.1109/ICPR.2002.1048320
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cascading style sheets Space technology Shape Feature extraction Human computer interaction Neural networks Handicapped aids Communication industry Computer industry Image recognition
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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