Hand gesture segmentation in uncontrolled environments with partition matrix and a spotting scheme based on hidden conditional random fields

Yi Yao, Chang Tsun Li

Research output: Book chapter/Published conference paperConference paper

5 Citations (Scopus)

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 languageEnglish
Title of host publicationProceedings of 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013)
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages842-846
Number of pages5
DOIs
Publication statusPublished - 2013
Event2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013) - Loisir Hotel & SPA Tower Naha, Naha, Okinawa, Japan
Duration: 05 Nov 201308 Nov 2013
http://www.am.sanken.osaka-u.ac.jp/ACPR2013/

Conference

Conference2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013)
CountryJapan
CityNaha, Okinawa
Period05/11/1308/11/13
Internet address

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    Yao, Y., & Li, C. T. (2013). Hand gesture segmentation in uncontrolled environments with partition matrix and a spotting scheme based on hidden conditional random fields. In Proceedings of 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR 2013) (pp. 842-846). [6778449] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ACPR.2013.153