Iterative Machine-Learning-Based Method of Selecting Encoder Parameters for Speed-Bitrate Tradeoff

Modern codecs offer numerous settings that can alter the encoding process. Multiobjective video encoding optimization has been studied in various works, but the whole encoder's option space was never considered. In this paper, we present a method for multiobjective encoding optimization in terms of relative video bitrate and encoding speed over the entire option space for a given encoder.