A framework for real-time hand gesture recognition in uncontrolled environments with partition matrix model based on hidden conditional random fields

Yi Yao, Chang Tsun Li

Research output: Book chapter/Published conference paperConference paper

1 Citation (Scopus)

Abstract

The main obstructions of making hand gesture recognition methods robust in real-world applications are the challenges from the uncontrolled environments, including: gesturing hand out of the scene, pause during gestures, complex background, skin-coloured regions moving in background, performers wearing short sleeve and face overlapping with hand. Therefore, a framework for real-time hand gesture recognition in uncontrolled environments is proposed in this paper. A novel tracking scheme is proposed to track multiple hand candidates in unconstrained background, and a weighting model for gesture classification based on Hidden Conditional Random Fields which takes trajectories of multiple hand candidates under different frame rates into consideration is also introduced. The framework achieved invariance under change of scale, speed and location of the hand gestures. The Experimental results of the proposed framework on Palm Graffiti Digits database and Warwick Hand Gesture database show that it can perform well in uncontrolled environments.
Original languageEnglish
Title of host publicationProceedings: 2013 IEEE International Conference on Systems, Man, and Cybernetics SMC 2013
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1205-1210
Number of pages6
ISBN (Print)9780769551548
DOIs
Publication statusPublished - 2013
Event2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013) - Midland Hotel, Manchester, United Kingdom
Duration: 13 Oct 201316 Oct 2013
https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=20015

Conference

Conference2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013)
Abbreviated titleCyber Systems Enabling Knowledge Integration: The Smart Response to Emerging Societal Challenges
CountryUnited Kingdom
CityManchester
Period13/10/1316/10/13
OtherSMC 2013 targets advances in Systems Science and Engineering Human-machine Systems and Cybernetics involving state-of-the-art technologies interacting with humans to provide an enriching experience and thereby improving the quality of lives including theories, methodologies and emerging applications.
Internet address

Fingerprint Dive into the research topics of 'A framework for real-time hand gesture recognition in uncontrolled environments with partition matrix model based on hidden conditional random fields'. Together they form a unique fingerprint.

  • Cite this

    Yao, Y., & Li, C. T. (2013). A framework for real-time hand gesture recognition in uncontrolled environments with partition matrix model based on hidden conditional random fields. In Proceedings: 2013 IEEE International Conference on Systems, Man, and Cybernetics SMC 2013 (pp. 1205-1210). [6721962] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SMC.2013.209