Feasibility of Neural Radiance Fields for Crime Scene Video Reconstruction
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909251590422528 |
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| author | Malik, Shariq Nadeem Chee, Min Hao Perera, Dayan Mario Anthony Lim, Chern Hong |
| author_facet | Malik, Shariq Nadeem Chee, Min Hao Perera, Dayan Mario Anthony Lim, Chern Hong |
| contents | This paper aims to review and determine the feasibility of using variations of NeRF models in order to reconstruct crime scenes given input videos of the scene. We focus on three main innovations of NeRF when it comes to reconstructing crime scenes: Multi-object Synthesis, Deformable Synthesis, and Lighting. From there, we analyse its innovation progress against the requirements to be met in order to be able to reconstruct crime scenes with given videos of such scenes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_08795 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Feasibility of Neural Radiance Fields for Crime Scene Video Reconstruction Malik, Shariq Nadeem Chee, Min Hao Perera, Dayan Mario Anthony Lim, Chern Hong Computer Vision and Pattern Recognition This paper aims to review and determine the feasibility of using variations of NeRF models in order to reconstruct crime scenes given input videos of the scene. We focus on three main innovations of NeRF when it comes to reconstructing crime scenes: Multi-object Synthesis, Deformable Synthesis, and Lighting. From there, we analyse its innovation progress against the requirements to be met in order to be able to reconstruct crime scenes with given videos of such scenes. |
| title | Feasibility of Neural Radiance Fields for Crime Scene Video Reconstruction |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2407.08795 |