Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images

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 th...

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Autore principale:	Wetzel, Johannes
Natura:	Online
Lingua:	inglese
Pubblicazione:	KIT Scientific Publishing 2022
Soggetti:	probabilistische Personendetektion Netzwerk von 3D-Sensoren Tiefenbilder inverses Problem joint multi-view person detection depth sensor indoor surveillance mean-field variational inference vertical top-view indoor pedestrian detection thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
Accesso online:	ONIX_20220718_9783731511779_115
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