schoonen, twan (2018) Counting people in videos. Bachelor's Thesis, Computing Science.
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Abstract
In a more and more media filled world, automation is needed for analyzing media sources. In this thesis we focus on counting people in video collections. These videos collection are to large to watch manually and have a low resolution. We compare 2 different face detection techniques and 4 different image comparison techniques. With the optimal setting we achieve a reduction rate of 95.36% on average.
| Item Type: | Thesis (Bachelor's Thesis) |
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| Supervisor name: | Sobiecki, A. and Telea, A.C. |
| Degree programme: | Computing Science |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 17 Jul 2018 |
| Last Modified: | 17 Jul 2018 14:30 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/17900 |
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