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Developing task-specific RBF hand gesture recognition
chapter
posted on 2023-06-07, 14:02 authored by A.J. Howell, Kingsley Sage, Hilary BuxtonIn this paper we develop hand gesture learning and recognition techniques to be used in advanced vision applications, such as the ActIPret system for understanding the activities of expert operators for education and training. Radial Basis Function (RBF) networks have been developed for reactive vision tasks and work well, exhibiting fast learning and classification. Specific extensions of our existing work to allow more general 3-D activity analysis reported here are: 1) action-based representation in a hand frame-of-reference by pre-processing of the trajectory data; 2) adaptation of the time-delay RBF network scheme to use this relative velocity information from the 3-D trajectory information in gesture recognition; and 3) development of multi-task support in the classifications by exploiting prototype similarities extracted from different combinations of direction (target tower) and height (target pod) for the hand trajectory.
History
Publication status
- Published
Journal
Gesture WorkshopPublisher
Springer Berlin / HeidelbergVolume
2915Page range
269-276Pages
556.0Book title
Gesture-Based Communication in Human-Computer InteractionPlace of publication
Berlin, GermanyISBN
9783540210726Series
Lecture Notes in Computer ScienceDepartment affiliated with
- Informatics Publications
Full text available
- No
Peer reviewed?
- Yes