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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2401.12182 |
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| _version_ | 1866910304883965952 |
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| author | Robinson, Michael Stein, Michael Owen, Henry S. |
| author_facet | Robinson, Michael Stein, Michael Owen, Henry S. |
| contents | This article addresses the problem of multi-object tracking by using a non-deterministic model of target behaviors with hard constraints. To capture the evolution of target features as well as their locations, we permit objects to lie in a general topological target configuration space, rather than a Euclidean space. We obtain tracker performance bounds based on sample rates, and derive a flexible, agnostic tracking algorithm. We demonstrate our algorithm on two scenarios involving laboratory and field data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_12182 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Tracking before detection using partial orders and optimization Robinson, Michael Stein, Michael Owen, Henry S. Dynamical Systems Computational Engineering, Finance, and Science 37N99 This article addresses the problem of multi-object tracking by using a non-deterministic model of target behaviors with hard constraints. To capture the evolution of target features as well as their locations, we permit objects to lie in a general topological target configuration space, rather than a Euclidean space. We obtain tracker performance bounds based on sample rates, and derive a flexible, agnostic tracking algorithm. We demonstrate our algorithm on two scenarios involving laboratory and field data. |
| title | Tracking before detection using partial orders and optimization |
| topic | Dynamical Systems Computational Engineering, Finance, and Science 37N99 |
| url | https://arxiv.org/abs/2401.12182 |