Abstract
With the development of wireless network and the improvement of mobile device capability, video streaming is more and more widespread in such an environment. Under the condition of limited resource and inherent constraints, appropriate video adaptations have become one of the most important and challenging issues in wireless multimedia applications. In this paper, we propose a novel content-aware video adaptation in order to effectively utilize resource and improve visual perceptual quality. First, the attention model is derived from analyzing the characteristics of brightness, location, motion vector, and energy features in compressed domain to reduce computation complexity. Then, through the integration of attention model, capability of client device and correlational statistic model, attractive regions of video scenes are derived. The information object- (IOB-) weighted rate distortion model is used for adjusting the bit allocation. Finally, the video adaptation scheme dynamically adjusts video bitstream in frame level and object level. Experimental results validate that the proposed scheme achieves better visual quality effectively and efficiently.
Highlights
With the development of wireless network and the improvement of mobile device capability, for mobile users, the desire to access videos is becoming stronger
The problem addressed in this paper is to utilize content information for improving the quality of a transmitted video bitstream subject to low-bitrate constraints, which especially applies to mobile devices in wireless network environment
In frame level bit allocation, we take into account the average importance attention value (AIMP), average motion mean (AMM), and average motion variance (AMV), which are obtained by aggregating those values of all frames within a GOP
Summary
With the development of wireless network and the improvement of mobile device capability, for mobile users, the desire to access videos is becoming stronger. Lai et al proposed a content-based video streaming method based on visual attention model to efficiently utilize network bandwidth and achieve better subjective video quality [13]. There have been many approaches for adapting visual contents, most of them focus only on developing visual attention model in order to meet the bit-rate constraint and to achieve high visual quality without considering the device capability. The problem addressed in this paper is to utilize content information for improving the quality of a transmitted video bitstream subject to low-bitrate constraints, which especially applies to mobile devices in wireless network environment. Bitrate allocation and adaptation assignment scheme is performed according to the content information in order to achieve better visual quality and avoid unnecessary resource waste under low-bitrate constraint.
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