Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images
(Sprache: Englisch)
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...
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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.
Bibliographische Angaben
- Autor: Johannes Wetzel
- 2022, 204 Seiten, mit Abbildungen, Maße: 14,8 x 21 cm, Kartoniert (TB), Englisch
- Verlag: KIT Scientific Publishing
- ISBN-10: 3731511770
- ISBN-13: 9783731511779
Sprache:
Englisch
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