Power-aware Regions-of-Interest Computational Resource Allocation for Mobile Sign Language Video Encoding

Abstract

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.