Crowd estimation in images
This final-year project explores the feasibility and effectiveness of the Point-Query Quadtree (PET) crowd estimation method on a localised (Singaporean) dataset. As borders open and crowd restrictions ease, there is need for such technologies to prevent an onset of crowd crush or stampede situation...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/174984 |
| _version_ | 1826120618815258624 |
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| author | Chen, Kang Ming |
| author2 | Cham Tat Jen |
| author_facet | Cham Tat Jen Chen, Kang Ming |
| author_sort | Chen, Kang Ming |
| collection | NTU |
| description | This final-year project explores the feasibility and effectiveness of the Point-Query Quadtree (PET) crowd estimation method on a localised (Singaporean) dataset. As borders open and crowd restrictions ease, there is need for such technologies to prevent an onset of crowd crush or stampede situations, which although may be few and far between, but can have devastating long-term consequences to many people. Two extensions to the PET method incorporating depth estimation using the DepthAnything framework will be assessed and analysed for its efficacy and improvements. In the modifications done, we show that a 33% decrease in mean absolute error is possible, honing the scalability and effectiveness of PET and with modifications. |
| first_indexed | 2024-10-01T05:19:43Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/174984 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:19:43Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1749842024-05-10T15:40:54Z Crowd estimation in images Chen, Kang Ming Cham Tat Jen School of Computer Science and Engineering ASTJCham@ntu.edu.sg Computer and Information Science Computer vision Image recognition Crowd counting Crowd estimation This final-year project explores the feasibility and effectiveness of the Point-Query Quadtree (PET) crowd estimation method on a localised (Singaporean) dataset. As borders open and crowd restrictions ease, there is need for such technologies to prevent an onset of crowd crush or stampede situations, which although may be few and far between, but can have devastating long-term consequences to many people. Two extensions to the PET method incorporating depth estimation using the DepthAnything framework will be assessed and analysed for its efficacy and improvements. In the modifications done, we show that a 33% decrease in mean absolute error is possible, honing the scalability and effectiveness of PET and with modifications. Bachelor's degree 2024-05-06T02:34:39Z 2024-05-06T02:34:39Z 2024 Final Year Project (FYP) Chen, K. M. (2024). Crowd estimation in images. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/174984 https://hdl.handle.net/10356/174984 en SCSE23-0029 application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Computer vision Image recognition Crowd counting Crowd estimation Chen, Kang Ming Crowd estimation in images |
| title | Crowd estimation in images |
| title_full | Crowd estimation in images |
| title_fullStr | Crowd estimation in images |
| title_full_unstemmed | Crowd estimation in images |
| title_short | Crowd estimation in images |
| title_sort | crowd estimation in images |
| topic | Computer and Information Science Computer vision Image recognition Crowd counting Crowd estimation |
| url | https://hdl.handle.net/10356/174984 |
| work_keys_str_mv | AT chenkangming crowdestimationinimages |