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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2509.04370 |
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| _version_ | 1866911138513420288 |
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| author | Cohen, Dor Efrosman, Inga Aperstein, Yehudit Apartsin, Alexander |
| author_facet | Cohen, Dor Efrosman, Inga Aperstein, Yehudit Apartsin, Alexander |
| contents | First responders widely adopt body-worn cameras to document incident scenes and support post-event analysis. However, reviewing lengthy video footage is impractical in time-critical situations. Effective situational awareness demands a concise visual summary that can be quickly interpreted. This work presents a computer vision pipeline that transforms body-camera footage into informative panoramic images summarizing the incident scene. Our method leverages monocular Simultaneous Localization and Mapping (SLAM) to estimate camera trajectories and reconstruct the spatial layout of the environment. Key viewpoints are identified by clustering camera poses along the trajectory, and representative frames from each cluster are selected. These frames are fused into spatially coherent panoramic images using multi-frame stitching techniques. The resulting summaries enable rapid understanding of complex environments and facilitate efficient decision-making and incident review. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_04370 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Stitching the Story: Creating Panoramic Incident Summaries from Body-Worn Footage Cohen, Dor Efrosman, Inga Aperstein, Yehudit Apartsin, Alexander Computer Vision and Pattern Recognition First responders widely adopt body-worn cameras to document incident scenes and support post-event analysis. However, reviewing lengthy video footage is impractical in time-critical situations. Effective situational awareness demands a concise visual summary that can be quickly interpreted. This work presents a computer vision pipeline that transforms body-camera footage into informative panoramic images summarizing the incident scene. Our method leverages monocular Simultaneous Localization and Mapping (SLAM) to estimate camera trajectories and reconstruct the spatial layout of the environment. Key viewpoints are identified by clustering camera poses along the trajectory, and representative frames from each cluster are selected. These frames are fused into spatially coherent panoramic images using multi-frame stitching techniques. The resulting summaries enable rapid understanding of complex environments and facilitate efficient decision-making and incident review. |
| title | Stitching the Story: Creating Panoramic Incident Summaries from Body-Worn Footage |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.04370 |