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.
Umfang: XXI, 167 S.
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Wetzel, J. 2022. Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000144094
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Veröffentlicht am 12. Juli 2022