AI-Based Content Adaptive Video Compression

The rapid evolution of video resolution has significantly increased the video bitrate requirement, making data transfer a challenging task for data-intensive applications like video conferencing, cloud gaming and game streaming. With the rise of machine learning, studies have shown the potential of embedding conventional video compression algorithms with AI-based methods to enhance their performance. This research project aims to explore the potential features from the input video that can be leveraged by machine learning algorithms to predict the optimal parameters used in the video compression process, with the goal of maximizing the quality of the decompressed video under fixed bitrate constrain.

Faculty Supervisor:

Qiang Sun

Student:

Partner:

AMD Canada

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program: