Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images
In: Forschungsberichte aus der Industriellen Informationstechnik; (2022)
Online
E-Book
- 204
Zugriff:
In this work, the task of wide-area indoor people detection in a network of depth sensors is examined. In particular, we investigate how the redundant and complementary multi-view information, including the temporal context, can be jointly leveraged to improve the detection performance. We recast the problem of multi-view people detection in overlapping depth images as an inverse problem and present a generative probabilistic framework to jointly exploit the temporal multi-view image evidence.
| Titel: |
Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images
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| Autor/in / Beteiligte Person: | Wetzel, Johannes |
| Link: | |
| Quelle: | Forschungsberichte aus der Industriellen Informationstechnik; (2022) |
| Veröffentlichung: | Karlsruhe: KIT Scientific Publishing, 2022 |
| Medientyp: | E-Book |
| Umfang: | 204 |
| ISBN: | 978-3-7315-1177-9 (print) ; 3-7315-1177-0 (print) |
| ISSN: | 2190-6629 (print) |
| DOI: | 10.5445/KSP/1000144094 |
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