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Hand gesture segmentation in uncontrolled environments with partition matrix and a spotting scheme based on hidden conditional random fields
Hand gesture segmentation is the task of interpreting and spotting meaningful hand gestures from continuous hand gesture sequences with non-sign transitional hand movements. In real world scenarios, challenges from the unconstrained environments can largely affect the performance of gesture segmentation. In this paper, we propose a gesture spotting scheme which can detect and monitor all eligible hand candidates in the scene, and evaluate their movement trajectories with a novel method called Partition Matrix based on Hidden Conditional Random Fields. Our experimental results demonstrate that the proposed method can spot meaningful hand gestures from continuous gesture stream with 2-4 people randomly moving around in an uncontrolled background.
History
Event
International Association for Pattern Recognition. Conference (2nd : 2013 : Naha, Japan)Series
International Association for Pattern Recognition ConferencePagination
842 - 846Publisher
Institute of Electrical and Electronics EngineersLocation
Naha, JapanPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2013-11-05End date
2013-11-08ISBN-13
978-1-4799-2190-4Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2013, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
ACPR 2013 : Proceedings of the 2013 2nd IAPR Asian Conference on Pattern RecognitionUsage metrics
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