DocumentCode :
530764
Title :
Applying edit distance to hand language video
Author :
Zhang, Shilin ; Wang, Hai
Author_Institution :
Network & Inf. Manage. Center, North China Univ. of Technol., Beijing, China
Volume :
3
fYear :
2010
fDate :
24-26 Aug. 2010
Firstpage :
212
Lastpage :
215
Abstract :
We present a revised method to compute the similarity of traditional string edit distance in this paper. Because this method lacks some types of normalization, it would bring some computation errors when the sizes of the strings that are compared are variable. In order to compute the edit distance, a new algorithm is introduced. In this paper, we solve the retrieval problem by high level features used by hand language trajectory and compare the similarity by our revised string edit distance algorithms. Trajectory based video retrieval is widely explored in recent years by many excellent researchers. Experiments in trajectory-based sign language video retrieval are presented in our paper at last, revealing that our revised edit distance algorithm consistently provide better results than classical edit distances.
Keywords :
computational complexity; content-based retrieval; gesture recognition; string matching; video retrieval; hand language trajectory; string edit distance; trajectory-based sign language video retrieval; Databases; Hidden Markov models; Content based Video retrieval Hand language; Edit Distance; Introduction; Sign language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
Type :
conf
DOI :
10.1109/CMCE.2010.5610338
Filename :
5610338
Link To Document :
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