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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.13131 |
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| _version_ | 1866911780592156672 |
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| author | Hahn, Maximilian Egger, Bernhard |
| author_facet | Hahn, Maximilian Egger, Bernhard |
| contents | Statistical Shape Models of faces and various body parts are heavily used in medical image analysis, computer vision and visualization. Whilst the field is well explored with many existing tools, all of them aim at experts, which limits their applicability. We demonstrate the first tool that enables the convenient exploration of statistical shape models in the browser, with the capability to manipulate the faces in a targeted manner. This manipulation is performed via a posterior model given partial observations. We release our code and application on GitHub https://github.com/maximilian-hahn/exploreCOSMOS |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_13131 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | exploreCOSMOS: Interactive Exploration of Conditional Statistical Shape Models in the Web-Browser Hahn, Maximilian Egger, Bernhard Computer Vision and Pattern Recognition Statistical Shape Models of faces and various body parts are heavily used in medical image analysis, computer vision and visualization. Whilst the field is well explored with many existing tools, all of them aim at experts, which limits their applicability. We demonstrate the first tool that enables the convenient exploration of statistical shape models in the browser, with the capability to manipulate the faces in a targeted manner. This manipulation is performed via a posterior model given partial observations. We release our code and application on GitHub https://github.com/maximilian-hahn/exploreCOSMOS |
| title | exploreCOSMOS: Interactive Exploration of Conditional Statistical Shape Models in the Web-Browser |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2402.13131 |