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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Main Author: | |
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Format: | Electronic Book Chapter |
Language: | English |
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Karlsruhe
KIT Scientific Publishing
2022
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Series: | Forschungsberichte aus der Industriellen Informationstechnik
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Subjects: | |
Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Wetzel, Johannes |4 auth | |
245 | 1 | 0 | |a Probabilistic Models and Inference for Multi-View People Detection in Overlapping Depth Images |
260 | |a Karlsruhe |b KIT Scientific Publishing |c 2022 | ||
300 | |a 1 electronic resource (204 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
490 | 1 | |a Forschungsberichte aus der Industriellen Informationstechnik | |
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a 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. | ||
540 | |a Creative Commons |f by-sa/4.0 |2 cc |4 http://creativecommons.org/licenses/by-sa/4.0 | ||
546 | |a English | ||
650 | 7 | |a Electrical engineering |2 bicssc | |
653 | |a probabilistische Personendetektion | ||
653 | |a Netzwerk von 3D-Sensoren | ||
653 | |a Tiefenbilder | ||
653 | |a inverses Problem | ||
653 | |a joint multi-view person detection | ||
653 | |a depth sensor indoor surveillance | ||
653 | |a mean-field variational inference | ||
653 | |a vertical top-view indoor pedestrian detection | ||
856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/20.500.12657/57538/1/9783731511779.pdf |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/90072 |7 0 |z DOAB: description of the publication |