NDLI: Human gesture recognition using orientation segmentation feature on random rorest

Content Provider	IEEE Xplore Digital Library
Author	Weihua Liu Yangyu Fan Tao Lei Zhong Zhang
Copyright Year	2014
Description	Author affiliation: Univ. of Texas at Arlington, Arlington, TX, USA (Zhong Zhang) \|\| Northwestern Polytech. Univ., Xi'an, China (Weihua Liu; Yangyu Fan; Tao Lei)
Abstract	In the field of gesture recognition, one of the major challenges lies in that different user may sign different style of gesture. Traditional exemplar-based methods are vulnerable to gesture scaling and hand location translating. To overcome such disadvantage, we propose an efficient and inexpensive solution for classifying hand gestures by defining an invariant feature and applying it on random forest. One of the prominent characteristics of gesture is the underlying sequence structure, which can be greatly distinguished from other gestures. Hence, direction of gesture sequence segments has been established as simple comparison features for training random forest classifier, and then predicting gestures at sign piece level. The property of this feature determines that our recognition method can invariant to gesture scaling and hand location translating. It is free to act gesture at any angular field of view and not subject to different acting style of signer. The results show that the performance of proposed method outweighs other state-of-art methods for gesture recognition.
Starting Page	480
Ending Page	484
File Size	2280125
Page Count	5
File Format	PDF
ISBN	9781479954018
e-ISBN	9781479954032
DOI	10.1109/ChinaSIP.2014.6889289
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Accuracy Hidden Markov models Invariant feature Gesture recognition Vegetation Random forest Trajectory Act style Gesture sequence Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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