Content-Adaptable ROI-Aware Video Storage for Power-Quality Scalable Mobile Streaming

Abstract

The demand for mobile video streams is constantly increasing. With this demand comes a need for mobile devices to receive more videos at ever increasing quality. However, due to the large size of video data and intensive computational requirements, video streaming requires frequent memory access that consume a substantial amount of mobile device power; as a result, the battery life of mobile devices is limited. In this paper, we present a video content-adaptable Region-of-Interest (ROI)-aware video storage technique that promotes power savings. During the video encoding process on the transmitting server, based on the macroblock variance and ROI characterization, the "macroblocks of interest" are identified and embedded in the encoded bitstream. In the decoding process, a new frame buffer with dynamic power-quality trade-off is presented to adapt to the macroblock characteristics during run-time. Results from the system-level and circuit-level simulations show that the proposed technique enables substantially more truncated bits and significant power savings while delivering similar or better video quality as compared to other state-of-theart solutions.

An Efficient Low Complexity Region-of-Interest Detection for Video Coding in Wireless Visual Surveillance

“…While in [30], the Canny ED is used as a low-cost edge detection method to extract the ROI prior to compression. ROI detection has also been a solution to control the memory usage [45], the bitrate [46], and the quality of the video encoder. This is accomplished by managing the bit allocation mechanisms, as shown in [47].…”

Approximate Memory for Low-Power Video Applications

“…to the embedded memory [1], [2], [3]. Accordingly, lowpower memory design is extremely important to support video applications on IoT devices.…”