Rate-distortion-prediction model for ultra-low latency video transmission

Thesis Proposal Details

Supervisor: Marco Cagnazzo

Creation Date: 09/10/2025 11:30

Description

Ultra-low latency video transmission can be achieved by using image prediction in order to reduce apparent latency. This comes at the cost of some additional distortion (extrapolation artifacts)

The goal of this thesis is to provide a reliable model to predict the global distortion of a video sequence as a function of the coding rate and the temporal distance of the prediction. 

The methodology includes: data acquisition campaign, choice of the model, and experimental validation. 

Dataset and methods

Dataset type: Already acquired data

Dataset description: We will use video sequences from public databases like MPEG, KITTI, etc.

List of Methods: video transmission video coding parametric model estimation

Tags
compression image prediction model rate-distortion video
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