Low-delay reliable video delivery for real-time immersive applications

点击翻译按钮获取中文摘要

Recent years have witnessed a rapid deployment of video devices, applications and systems, and this growth will only intensify. Large amounts of video data will be streamed in very innovative applications such as live immersive video (e.g., 360-degree video), visual remote machinery control, remote surgery and live inter-vehicular communications. A wide diversity of interactive video applications are deployed on heterogeneous networks, and ensuring the reliable delivery of video data, especially under low delay constraints, is highly challenging. Specifically, transmission errors and packet losses over wireless networks cause significant delays and visual quality degradation. Thus, in seeking to provide the best quality of experience to end users, the ability to transport video content in a fast and reliable manner constitutes one of the most crucial challenges for modern networks, such as 5G. This research program aims mainly to propose novel solutions to the problem of ensuring the reliable delivery of video data over heterogeneous networks, under very low delay constraints, in the context of immersive video applications. Specifically, the applicant and his team will create promising methods to protect video data against losses and transmission errors, in addition to methods to correct and repair video content. These will remove the need for retransmissions, which are undesirable or unsuitable for very low-delay applications. In this quest, they will pursue five research tracks. First, they will create new classes of forward error correction (FEC) methods suitable for low-delay interactive video applications. Second, they will propose a radically new approach combining their newly developed algorithms for correcting erroneous video packets, using the Cyclic Redundancy Check information, with these new FEC classes, to protect the system against both bit errors and packets losses. Third, they will develop new machine learning approaches to dynamically adapt the FEC parameters to the video content and ever-changing network conditions in order to ensure error-free video reconstruction while meeting delay constraints. Fourth, they will apply these technologies to the coding and delivery of tiles-based 360-degree video by exploiting coding tools found in the new versatile video coding (VVC)/H.266 standard. Finally, they will propose new deep-learning approaches to evaluate the quality of damaged and repaired videos. The advances provided by this research will significantly improve the quality and usability of interactive and immersive video services, as well as other delay-sensitive applications, and enable the emergence of unprecedented media experiences. As for their previous research, Canada will benefit strongly from the intellectual property and commercialization of the technologies therein and from the training of highly qualified personnel in the fast-growing field of immersive video.