DocumentCode :
2454614
Title :
A system for sign video retrieval
Author :
Zhang, Shilin ; Gu, Mei
Author_Institution :
Manage. Center, North China Univ. of Technol., Beijing, China
fYear :
2010
fDate :
24-27 Aug. 2010
Firstpage :
1385
Lastpage :
1389
Abstract :
In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands´ length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands´ dynamic features. Consequently, we segment the video frames by motion features. As for each segment, we generate a HMM. When a clip of hand language inputs, we also get the feature serials, and then we compare the possibility of the input serials in each HMM. Experiment results on a large of hand language videos show that our searching system performs much better than existing methods on hand language video searching systems. Compared with the traditional methods, our system reduces the average searching time by half and the searching precision has doubled.
Keywords :
Fourier analysis; gesture recognition; hidden Markov models; image motion analysis; image segmentation; video retrieval; Fourier figure descriptor; HMM; hand language recognition; hand language video searching systems; high level features; motion features; sign video retrieval; video frame segmentation; Computational modeling; Databases; Face; Feature extraction; Hidden Markov models; Image color analysis; Skin; Content-based video searching; DTW; HMM; Hand language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Education (ICCSE), 2010 5th International Conference on
Conference_Location :
Hefei
Print_ISBN :
978-1-4244-6002-1
Type :
conf
DOI :
10.1109/ICCSE.2010.5593751
Filename :
5593751
Link To Document :
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