From Far and Near: Perceptual Evaluation of Crowd Representations Across Levels of Detail
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908901124866048 |
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| author | Sun, Xiaohan O'Sullivan, Carol |
| author_facet | Sun, Xiaohan O'Sullivan, Carol |
| contents | In this paper, we investigate how users perceive the visual quality of crowd character representations at different levels of detail (LoD) and viewing distances. Each representation, including geometric meshes, image-based impostors, Neural Radiance Fields (NeRFs), and 3D Gaussians, exhibits distinct trade-offs between visual fidelity and computational performance. Our qualitative and quantitative results provide insights to guide the design of perceptually optimized LoD strategies for crowd rendering. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_20558 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Far and Near: Perceptual Evaluation of Crowd Representations Across Levels of Detail Sun, Xiaohan O'Sullivan, Carol Computer Vision and Pattern Recognition Graphics Human-Computer Interaction In this paper, we investigate how users perceive the visual quality of crowd character representations at different levels of detail (LoD) and viewing distances. Each representation, including geometric meshes, image-based impostors, Neural Radiance Fields (NeRFs), and 3D Gaussians, exhibits distinct trade-offs between visual fidelity and computational performance. Our qualitative and quantitative results provide insights to guide the design of perceptually optimized LoD strategies for crowd rendering. |
| title | From Far and Near: Perceptual Evaluation of Crowd Representations Across Levels of Detail |
| topic | Computer Vision and Pattern Recognition Graphics Human-Computer Interaction |
| url | https://arxiv.org/abs/2510.20558 |