Low-Complexity and Context-Aware Estimation of Spatial and Temporal Activity Parameters for Automotive Camera Rate Control

Abstract

Rate control in video compression adjusts the encoding parameters to reach a certain target bitrate for the encoded video. State-of-the-art rate controllers for hybrid video coding typically employ content-dependent video bitrate models and video quality metrics (VQMs). To capture the content characteristics, temporal and spatial video activity measures are determined from the raw video using computationally complex algorithms that require access to the uncompressed source video. In automotive deployments, however, full access to the uncompressed source video and the internal functions of video encoders is typically not possible. As a remedy, in this paper, we present a low-complexity approach to estimate the temporal activity (TA) and spatial activity (SA) measures for videos that are captured by a front-facing camera of a vehicle, based on the context information of the vehicle. To this end, we exploit information about the dynamics of the vehicle and other vehicles in the field-of-view of the front-facing camera. We apply the estimated TA and SA values to a video bitrate model and an objective VQM and use these models to solve the rate control problem to determine the optimal encoding settings for given bitrate constraints. The proposed low-complexity solution offers a similar accuracy in achieving rate constraints and similar perceptual quality characteristics as a solution that uses the computed TA and SA values, with the advantage that no access to the uncompressed source video stream or the internal functions of the video encoder is required.