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[null,"1.","Record Nr.",null,"UNINA9910584592103321"]
[null,null,"Autore",null,"Wetzel Johannes"]
[null,null,"Titolo",null,"Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images"]
[null,null,"Pubbl/distr/stampa",null,"Karlsruhe, : KIT Scientific Publishing, 2022"]
[null,null,"ISBN",null,"1000144094"]
[null,null,"Descrizione fisica",null,"1 online resource (204 p.)"]
[null,null,"Collana",null,"Forschungsberichte aus der Industriellen Informationstechnik"]
[null,null,"Soggetti",null,"Electrical engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","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."]