Improvement Tracking Dynamic Programming using Replication Function for Continuous Sign Language Recognition

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2014 by IJETT Journal
Volume-7 Number-3                          
Year of Publication : 2014
Authors : S. Ildarabadi , M. Ebrahimi , H. R. Pourreza
  10.14445/22315381/IJETT-V7P254

citation 

S. Ildarabadi , M. Ebrahimi , H. R. Pourreza , Article:Improvement Tracking Dynamic Programming using Replication Function for Continuous Sign Language Recognition , International Journal of Engineering Trends and Technology(IJETT), 7(3),97-101, published by seventh sense research group

Abstract

In this paper we used a Replication Function (R. F.) for improvement tracking with dynamic programming. The R. F. transforms values of gray level [0 255] to [0 1]. The resulting images of R. F. are more striking and visible in skin regions. The R. F. improves Dynamic Programming (D. P.) in overlapping hand and face. Results show that Tracking Error Rate 11% and Average Tracked Distance 7% reduced.

References

[1] G. R. Bradski: Computer Vision Face Tracking For Use in a Perceptual User Interface, Intel Technology Journal, Vol. Q2, pp. 15–26, 1998.

[2] D. Comaniciu, V. Ramesh & P. Meer: Real-Time Tracking of Non-Rigid Objects using Mean Shift. In IEEE Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 142–151, Hilton Head Island, South Carolina, USA, June 2000.

[3] Database RWTH-BOSTON-104 http://www-i6.informatik.rwth-aachen.de/~zahedi/database BOSTON201.html

[4] P. Dreuw. Appearance-Based Gesture Recognition, Master Thesis, Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Aachen, Germany, January, 2005.

[5] Dreuw, P., Stein, D., Deselaers, T., Rybach, D., Zahedi, M., Bungeroth, J., Ney, H.: Spoken language processing techniques for sign language recognition and translation. Technology and Dissability 20 (2008) 121-133

[6] Dreuw, P., Ney, H., Martinez, G., Crasborn, O., Piater, J., Miguel Moya, J., Wheatley, M.: The signspeak project - bridging the gap between signers and speakers. In: International Conference on Language Resources and Evaluation, Valletta, Malta (2010)

[7] P. Dreuw, J. Forster, and H. Ney. Tracking Benchmark Databases for Video-Based Sign Language Recognition. In ECCV International Workshop on Sign, Gesture, and Activity (SGA), Crete, Greece, September 2010.

[8] D. M. Gavrila: The Visual Analysis of Human Movement: A Survey, Computer Vision and Image Understanding, Vol. 73, No. 1, pp. 82–98, February 1999.

[9] M. Isard & A. Blake: CONDENSATION – conditional density propagation for visual tracking. International Journal of Computer Vision, Vol. 29, No. 1, pp. 5–28, August 1998.

[10] D. Rybach, Appearance-Based Features for Automatic Continuous Sign Language Recognition. Master Thesis, Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Aachen, Germany, June, 2006.

[11] M. Zahedi, Robust Appearance-based Sign Language Recognition, Master Thesis, Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Aachen, Germany, 2007.

Keywords:
dynamic programming, machine vision, replication function, sign language, tracking.