Application-aware video coding architecture using camera and object motion-models

The proliferation of video consumption, especially over mobile devices, has created a demand for efficient interactive video applications and high-level video analysis. This is particularly significant in real-time applications and resource-limited scenarios. Pixel-domain video processing is often inefficient for many of these applications due to its complexity, whereas compressed domain processing offer fast but unreliable results. In order to achieve fast and effective video processing, this paper proposes a novel video encoding architecture that facilitate efficient compressed domain processing, while maintaining compliance with the mainstream coding standards. This is achieved by optimizing the accuracy of motion information embedded in the compressed video, in addition to compression efficiency. In a motion detection application, we demonstrate that the motion estimated by the proposed encoder can be directly used to extract object information, as opposed to conventionally coded video. The incurred rate distortion overheads can be weighed against the reduced processing required for video analysis targeting a wide spectrum of computer vision applications

JOINT GLOBAL MOTION ESTIMATION AND CODING FOR SCALABLE H.264/SVC HIGH-DEFINITION VIDEO STREAMS

This paper presents a joint indexing-coding approach applied to global camera motion detection in the scalable H.264/SVC compressed domain. Our goal is to facilitate and to improve indexing in the MPEG compressed domain, if necessary by modifying the original coded stream, without losing compatibility with the standard. In frames with very noisy motion vector fields, we use the global motion information obtained by analyzing the raw video to modify the vectors of chosen macroblocks. This results in slightly decreased coding efficiency, but improved and more reliable indexing results in the compressed domain