Abstract
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.
Original language | English |
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Title of host publication | Proceedings of 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013) |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 842-846 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 2013 |
Event | 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013) - Loisir Hotel & SPA Tower Naha, Naha, Okinawa, Japan Duration: 05 Nov 2013 → 08 Nov 2013 http://www.am.sanken.osaka-u.ac.jp/ACPR2013/ |
Conference
Conference | 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013) |
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Country | Japan |
City | Naha, Okinawa |
Period | 05/11/13 → 08/11/13 |
Internet address |