A workload prediction model for decoding mpeg video and its application to workload-scalable transcoding

Abstract

Multimedia playback is restricted by the processing power of mobile devices, and in particular, the playback quality can be degraded due to insufficient processing power. To address this problem, we propose a new workload-scalable transcoding scheme which converts a pre-recorded video bitstream into a new video bitstream that satisfies the device's workload constraint, while keeping the transcoding distortion minimal. The key of this proposed transcoding scheme lies on a new workload prediction model, which is fast, accurate and is generic enough to apply to different video formats, decoder implementations and target platforms. The main contributions of this paper include 1) a workload prediction model for decoding MPEG video based on an offline bitstream analysis method; 2) a transcoding scheme that uses the proposed model to control the decoding workload on the target device. To facilitate our transcoding scheme, we have proposed a compressed domain distortion measure (CDDM) that takes effects from both frames per second (fps) and bits per frame (bpf) into consideration. CDDM ensures the transcoded video bitstream to have the best playback quality given the device's workload constraint. Both the workload prediction model and the transcoding scheme are evaluated experimentally. Copyright 2007 ACM.