In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
will defend his proposal
Compression Artifact Removal for Improved Video Analytics
AbstractVideo compression algorithms are pervasively applied at the camera level prior to video transmission due to bandwidth constraints, thereby reducing the quality of video available for automated video analytics. These artifacts may lead to decreased performance of some core applications in video surveillance systems such as object detection. To remove such distortions during video decoding, it is required to recover original video frames from distorted ones. To this end, we developed deep learning-based approaches for the compression artifact removal task under different levels of video compression. Experiments on self-collected data show that our methods can be applied as a pre-processing step for the object-detection task in practical, non-idealized applications where quality distortions may be present.
Date: Friday, May 01, 2020
Time: 11:00 AM - 12:00 PM
Place: Online Presentation - MS Teams
Advisors: Dr. Shishir K. Shah
Faculty, students, and the general public are invited.