Thesis Topic Details

Topic ID:
616
Title:
Robust Background and Foreground Analysis for Detecting and Tracking Moving Objects in Surveillance Video.
Supervisor:
Jian Zhang
Research Area:
Computer Vision
Associated Staff
Assessor:
Xuemin Lin
Topic Details
Status:
Active
Type:
Development
Programs:
CS CE BIOM BINF SE
Group Suitable:
No
Industrial:
Pre-requisites:
C++ programming. Advanced Math
Description:
The ultimate goal of any video surveillance system is to automatically understand and detect events of interest happening at a monitored site. Such a high-level task requires some low-level computer vision tasks to supply necessary information. The goal of this project is to utilize a recently proposed nonparametric Kernel Density Estimation (KDE) based algorithm to analyze the background and foreground to robustly detect moving objects out of dynamic environment and track their movement under occlusion situations.

The knowledge you learned from the computer and engineering courses, such as computer vision, signal processing, and statistics theory will gain plenty practice from this project. Your programming skills will also be developed as you will develop a demo in software.
Comments:
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