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Optical Engineering

Fuzzy-based latent-dynamic conditional random fields for continuous gesture recognition
Author(s): Shengjun Zhang; Xiaohai He; Qizhi Teng
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Paper Abstract

We show an original method for automatic hand gesture recognition that makes use of fuzzified latent-dynamic conditional random fields (LDCRF). In this method, fuzzy linguistic variables are used to model the features of hand gestures and then to modify the potential function in LDCRFs. By combining LDCRFs and fuzzy sets, these fuzzy-based LDCRFs (FLDCRF) have the advantages of LDCRFs in sequence labeling along with the advantage of retaining the imprecise character of gestures. The efficiency of the proposed method was tested with unsegmented gesture sequences in three different hand gesture data sets. The experimental results demonstrate that FLDCRFs compare favorably with support vector machines, hidden conditional random fields, and LDCRFs on hand gesture recognition tasks.

Paper Details

Date Published: 5 June 2012
PDF: 9 pages
Opt. Eng. 51(6) 067202 doi: 10.1117/1.OE.51.6.067202
Published in: Optical Engineering Volume 51, Issue 6
Show Author Affiliations
Shengjun Zhang, Sichuan Univ. (China)
Xiaohai He, Sichuan Univ. (China)
Qizhi Teng, Sichuan Univ. (China)

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