VAAC-IM: Motion-Aware Viewing Area Adaptive Control in Immersive Media Transmission

Han Xiao, Changqiao Xu, Chuxing Fang, Wendong Wang, Shujie Yang, Zhenhui Yuan, Luigi Alfredo Grieco

Abstract: Viewport in immersive media corresponds to the field of view (FoV), playing a critical role in both data transmission volume and user experience. However, instantaneous and highly dynamic interactions often conflict with segment-based transmission modes, resulting in substantial redundant data transmission and wastage of valuable resources. In this paper, we analyze data from an open-source dataset and our self-collected records to investigate the interactive characteristics of viewers in immersive scenes, including focus time, viewing area scope, movement direction, and tile access probability. Based on empirical statistical inference, we innovatively introduce the concept of an irregular, expandable, and directional extended field of view (EoV) to describe the dynamically variable area mimicking human visual motion. Furthermore, we propose a motion-aware tile-based adaptive control scheme for viewing areas, named VAAC-IM, designed to enable flexible transmission of immersive media. Specifically, we developed an FoV prediction model based on ConvLSTM, leveraging spatiotemporal features from historical viewing records to provide advanced predictions of visual motion preferences. Subsequently, we model the viewing area control process as a constrained submodular minimization problem, dynamically managing irregular EoV area using marginal effects. Finally, we perform a comprehensive validation. The results demonstrate that VAAC-IM significantly enhances performance in terms of reducing black edge coverage, minimizing data volume, lowering latency, and improving overall user experience.

External IDs:dblp:journals/tcsv/XiaoXFWYYG25