Content-adaptive cross-layer optimized video processing using real-time feature feedback

Abstract

The objective of this research is to design a low-power video processing system capable of minimizing power consumption through graceful reduction of the quality of the processed signal. Methods for post-processing signal analysis are proposed for determining the presence and quality of features essential to the high-level application goals. Two applications, video encoding and object tracking, are selected for study based on their high demand on mobile platforms. Methods for scaling the complexity of the entire system are proposed by simultaneously scaling down the input signal and algorithms to focus computational effort on information salient to the application. A cross-layer control system is proposed for determining the optimal complexity scaling and dynamic voltage and frequency scaling. The control system will be charged with providing dynamic voltage and frequency scaling control information for accurate prediction of imminent throughput requirements, allowing for minimal power consumption while narrowly achieving the high-level application goals.