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

• Yazar: Wetzel, Johannes (auth)
• Materyal Türü: Elektronik Kitap Bölümü
• Dil: İngilizce
• Baskı/Yayın Bilgisi: Karlsruhe KIT Scientific Publishing 2022
• Seri Bilgileri: Forschungsberichte aus der Industriellen Informationstechnik
• Konular: Electrical engineering; 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
• Online Erişim: DOAB: download the publication; DOAB: description of the publication

Özet

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.

Fiziksel Özellikler

1 electronic resource (204 p.)

ISBN

KSP/1000144094
9783731511779

Erişim

Open Access