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

Rate control in video compression adjusts the encoding parameters to reach a certain target bit rate for the encoded video. State-of-the-art rate controllers for hybrid video coding typically employ content-dependent video bit rate models and video quality metrics. To capture the content characteristics, temporal and spatial video activity measures are determined from the raw video using computationally complex algorithms, which 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 temporal and spatial activity measures for videos, which are captured by a front-facing camera of a vehicle, based on 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 temporal and spatial activity values to a video bit rate model and an objective video quality metric and use these models to solve the rate control problem to determine optimal encoding settings for given bit rate constraints. The proposed low-complexity solution offers a similar accuracy in achieving rate constraints and similar perceptual quality characteristics as a solution which uses the computed temporal and spatial activity values, with the advantage that no access to the uncompressed source video stream or the internal functions of the video encoder is required.