PhD Defense: "Towards Prediction Optimality in Video Compression and Networking"

Shunyao Li

February 27th (Tuesday), 12:00pm
Engineering Science Building (ESB), Rm 2001

In modern video compression and communication systems, prediction is one of the key schemes to exploit spatial and temporal redundancies. However, current approaches are suboptimal as they do not fully exploit the spatial and temporal correlations within signals. This talk focuses on the optimal prediction algorithms that fully utilize the correlations, and the optimal design of predictors that accounts for the rich variety of video statistics as well as the instability due to quantization error propagation in the closed-loop video coding system. Complementary to predictive coding, we also expand the design framework to the general predictive coding system, focusing on the optimal transform design that spatially de-correlates the residual data, leading to better compactness and compression performance.

The contributions in this talk cover the topics of spatial (intra) prediction, temporal (inter) prediction, the layered prediction in scalable coding and transform design. The contributions have been proposed to or accepted in multiple video coding standardization efforts including the Moving Picture Experts Group (MPEG) and the Alliance for Open Media (AOM), and have provided significant improvements in the video compression performance.

About Shunyao Li:

Photo of Shunyao Li Shunyao Li is a graduate student in the department of Electrical and Computer Engineering at University of California, Santa Barbara. She received the B.S. degree in electronic engineering from Tsinghua University, Beijing, China in 2013, and the M.S. degree in Electrical and Computer Engineering in 2014 from UCSB. She was a research intern with LG Electronics USA in the summer of 2014, and interned with Google in the summer of 2015, 2016 and 2017. Her research interests include video compression and networking.

Hosted by: Professor Kenneth Rose, Signal Compression Lab