Earticle

초록

영어

The primary challenge to design a mobile sign language communication system is overcoming the limitation of battery power. A scheme which allocates the computational resource of the encoder adaptive to available battery power and deaf people’s visual system is proposed. In the scheme, encoding levels which determine number of reference frames and search range are adaptively selected according to the battery power and frame complexity at frame level. Then possible partition mode and quantization parameter are adaptively adjusted at the macro block (MB) level according to the relative priority of each MB. Experimental results show that the proposed algorithm obtains better peak-signal-noise-rate of face and hands that improves the intelligibility of sign language video. Encoding time can be saved by up to 89.4% compared to the standard H.264 encoder. Increased bit rate of the proposed algorithm is less than 5%, which is negligible.

목차

Abstract
 1. Introduction
 2. System architecture
 3. Frame-level Computational Resource Allocation with Consideration of Power Consumption and Frame Complexity
 4. MB-level Computational Resource and Bit Allocation with Consideration of Deaf People’s Visual System
  4.1. Fast ROI detection for Sign Language Video
  4.2. ROI based Computational Power and Bits Allocation
 5. Experimental Results
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Xiaolei Chen [ School of Electrical and Information Engineering Lanzhou University of Technology, Lanzhou, P. R. China ]
• Aihua Zhang [ School of Electrical and Information Engineering Lanzhou University of Technology, Lanzhou, P. R. China ]
• Xinzhu Yang [ School of Mechanical Engineering Lanzhou Jiaotong University, Lanzhou, P. R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605