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: |
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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. |
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Comments: |
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| Past Student Reports | ||
| No Reports Available. Contact the supervisor for more information.
Check out all available reports in the CSE Thesis Report Library. NOTE: only current CSE students can login to view and select reports to download. |
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