模式识别与人工智能
Thursday, Apr. 3, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
  2014, Vol. 27 Issue (8): 741-749    DOI:
Researches and Applications Current Issue| Next Issue| Archive| Adv Search |
Chinese Sign Language Recognition Method Based on Depth Image Information and SURF-BoW
YANG Quan, PENG Jin-Ye
School of Information Science and Technology, Northwest University, Xi'an 710127

Download: PDF (956 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  To realize the accurate recognition of sign language in the video, an algorithm based on depth image CamShift(DI_CamShift) and speeded up robust features-bag of words (SURF-BoW) is proposed. Kinect is used as the sign language video capture device to obtain both of the color video and depth image information of sign language gestures. Firstly, spindle direction angle and mass center position of the depth images are calculated and the search window is adjusted to track gesture. Next, an OTSU algorithm based on depth integral image is used for gesture segmentation, and the SURF features are extracted. Finally, SURF-BoW is built as the feature of sign language and SVM is utilized for recognition. The best recognition rate of single manual alphabet reaches 99.37%, and the average recognition rate is up to 96.24%.
Key wordsDepth Image CamShift(DI_CamShift)      Speeded Up Robust Features-Bag of Words(SURF-BoW)      Depth Image      Sign Language Recognition     
Received: 24 April 2013     
ZTFLH: TP311  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
YANG Quan
PENG Jin-Ye
Cite this article:   
YANG Quan,PENG Jin-Ye. Chinese Sign Language Recognition Method Based on Depth Image Information and SURF-BoW[J]. , 2014, 27(8): 741-749.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2014/V27/I8/741
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn