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Real time large vocabulary continuous sign language recognition based on OP/Viterbi algorithm

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Up to now, continuous sign language recognition is mainly based on statistical methods, especially Hidden Markov Models (HMM) and Viterbi-Beam searching. However, the recognition speed often gets unacceptable with an increased vocabulary, which could cause a long time delay that is not fit for the real time recognition system. To speed up the recognition process, we present a method using One-Pass (OP) pre-searching before Viterbi recognition. The experiments are processed in the large vocabulary database. Results show that the average recognition speed of OP/Viterbi approach can get a notable raise comparing with the single frame 's without reducing too much recognition accuracy.

Original languageEnglish
Title of host publicationTrack C
Subtitle of host publicationApplications and Robotics Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages312-315
Number of pages4
ISBN (Print)0769525210, 9780769525211
DOIs
StatePublished - 2006
Externally publishedYes
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
Duration: 20 Aug 200624 Aug 2006

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Conference

Conference18th International Conference on Pattern Recognition, ICPR 2006
Country/TerritoryChina
CityHong Kong
Period20/08/0624/08/06

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