Recomposed realities: animating still images via patch clustering and randomness
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909664520699904 |
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| author | Juvonen, Markus Siltanen, Samuli |
| author_facet | Juvonen, Markus Siltanen, Samuli |
| contents | We present a patch-based image reconstruction and animation method that uses existing image data to bring still images to life through motion. Image patches from curated datasets are grouped using k-means clustering and a new target image is reconstructed by matching and randomly sampling from these clusters. This approach emphasizes reinterpretation over replication, allowing the source and target domains to differ conceptually while sharing local structures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_22556 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Recomposed realities: animating still images via patch clustering and randomness Juvonen, Markus Siltanen, Samuli Computer Vision and Pattern Recognition Image and Video Processing We present a patch-based image reconstruction and animation method that uses existing image data to bring still images to life through motion. Image patches from curated datasets are grouped using k-means clustering and a new target image is reconstructed by matching and randomly sampling from these clusters. This approach emphasizes reinterpretation over replication, allowing the source and target domains to differ conceptually while sharing local structures. |
| title | Recomposed realities: animating still images via patch clustering and randomness |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2506.22556 |