Thesis Topic Details
Topic ID: |
1017 | |
Title: |
Pedestrian Detection Using a Cascade of Boosted Classifiers | |
Supervisor: |
Jian Zhang | |
Research Area: |
Computer Vision | |
| Associated Staff | ||
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Assessor: |
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| Topic Details | ||
Status: |
Active | |
Type: |
R & D | |
Programs: |
CS CE BIOM BINF SE | |
Group Suitable: |
No | |
Industrial: |
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Pre-requisites: |
Digital image processing, Computer vision, C++ programming and Advanced Math (undergraduate level, Matlab. | |
Description: |
This project aims provide an implementation, verification and evaluation of a pedestrian detection framework proposed by Viola-Jones which is fast and robust under varying conditions by incorporating both motion and appearance in training a cascade classifiers. It is hoped that this project will serve as a foundation for other applications such as vehicle and cyclist detection; and incorporated with other image processing techniques such as tracking which would improve robustness and computational efficiency. |
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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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