Foveated Video Coding for Real-Time Streaming Applications

Abstract

Video streaming under real-time constraints is an increasingly widespread application. Many recent video encoders are unsuitable for this scenario due to theoretical limitations or run time requirements. In this paper, we present a framework for the perceptual evaluation of foveated video coding schemes. Foveation describes the process of adapting a visual stimulus according to the acuity of the human eye. In contrast to traditional region-of-interest coding, where certain areas are statically encoded at a higher quality, we utilize feedback from an eye-tracker to spatially steer the bit allocation scheme in real-time. We evaluate the performance of an H.264 based foveated coding scheme in a lab environment by comparing the bitrates at the point of just noticeable distortion (JND). Furthermore, we identify perceptually optimal codec parameterizations. In our trials, we achieve an average bitrate savings of 63.24% at the JND in comparison to the unfoveated baseline.