001     1034460
005     20241219210859.0
024 7 _ |a 10.34735/PED.2024.2
|2 doi
037 _ _ |a FZJ-2024-07226
041 _ _ |a English
100 1 _ |a Abubaker, Mohamad
|0 0009-0006-9119-4139
|b 0
245 _ _ |a RPEE-Heads: A Benchmark for Pedestrian Head Detection in Crowd Videos
260 _ _ |a Jülich
|c 2024
|b Forschungszentrum Jülich
336 7 _ |a MISC
|2 BibTeX
336 7 _ |a Dataset
|b dataset
|m dataset
|0 PUB:(DE-HGF)32
|s 1734594474_7060
|2 PUB:(DE-HGF)
336 7 _ |a Chart or Table
|0 26
|2 EndNote
336 7 _ |a Dataset
|2 DataCite
336 7 _ |a DATA_SET
|2 ORCID
336 7 _ |a ResearchData
|2 DINI
520 _ _ |a RPEE-Heads (Railway Platforms and Event Entrances-Heads) is a new benchmark for pedestrian head detection in crowded environments. It focuses on railway platforms and event entrances, where risks frequently arise. The benchmark aims to improve pedestrian head detection at railway platforms and event entrances, helping to develop accurate deep learning models for several crowd safety applications. It includes: 1) A dataset comprising 109913 head annotations across 1886 images, with an average of approximately 56.2 annotated heads per image. 2) An empirical comparative analysis of eight state-of-the-art deep learning algorithms for head detection was conducted across several publicly available image datasets and the newly introduced RPEE-Heads dataset. 3) An empirical study on head size’s impact on detection algorithms’ performance.
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5111
|c POF4-511
|f POF IV
|x 0
536 _ _ |a Pilotprojekt zur Entwicklung eines palästinensisch-deutschen Forschungs- und Promotionsprogramms 'Palestinian-German Science Bridge' (01DH16027)
|0 G:(BMBF)01DH16027
|c 01DH16027
|x 1
588 _ _ |a Dataset connected to DataCite
700 1 _ |a Alsadder, Zubayda
|0 0009-0008-2715-3345
|b 1
700 1 _ |a Abdelhaq, Hamed
|0 0000-0003-4803-6689
|b 2
700 1 _ |a Boltes, Maik
|0 P:(DE-Juel1)132064
|b 3
700 1 _ |a Alia, Ahmed
|0 P:(DE-Juel1)185971
|b 4
773 _ _ |a 10.34735/PED.2024.2
856 4 _ |u http://ped.fz-juelich.de/da/2024rpee_heads
909 C O |o oai:juser.fz-juelich.de:1034460
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910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)132064
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)185971
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5111
|x 0
914 1 _ |y 2024
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IAS-7-20180321
|k IAS-7
|l Zivile Sicherheitsforschung
|x 0
980 _ _ |a dataset
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IAS-7-20180321
980 _ _ |a UNRESTRICTED


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