Improving a real-time object detector with compact temporal information

Martin Ahrnbom, Morten Bornø Jensen, Kalle Åström, Mikael Nilsson, Håkan Ardö, Thomas B. Moeslund

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Resumé

Neural networks designed for real-time object detection have recently improved significantly, but in practice, look- ing at only a single RGB image at the time may not be ideal. For example, when detecting objects in videos, a foreground detection algorithm can be used to obtain compact temporal data, which can be fed into a neural network alongside RGB images. We propose an approach for doing this, based on an existing object detector, that re-uses pretrained weights for the processing of RGB images. The neural network was tested on the VIRAT dataset with annotations for object de- tection, a problem this approach is well suited for. The ac- curacy was found to improve significantly (up to 66%), with a roughly 40% increase in computational time.
OriginalsprogEngelsk
Titel2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop
Antal sider8
ForlagIEEE
Publikationsdato2017
Sider190-197
ISBN (Elektronisk)978-1-5386-1034-3
DOI
StatusUdgivet - 2017
Begivenhed2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop - PALAZZO DEL CINEMA - VENICE CONVENTION CENTER, Venice, Italien
Varighed: 22 okt. 201729 okt. 2017

Konference

Konference2017 IEEE International Conference on Computer Vision Workshop (ICCVW)
LokationPALAZZO DEL CINEMA - VENICE CONVENTION CENTER
LandItalien
ByVenice
Periode22/10/201729/10/2017
NavnIEEE International Conference on Computer Vision Workshops (ICCVW)
ISSN2473-9944

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Detectors
Neural networks
Processing
Object detection

Citer dette

Ahrnbom, M., Jensen, M. B., Åström, K., Nilsson, M., Ardö, H., & Moeslund, T. B. (2017). Improving a real-time object detector with compact temporal information. I 2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop (s. 190-197). IEEE. IEEE International Conference on Computer Vision Workshops (ICCVW) https://doi.org/10.1109/ICCVW.2017.31
Ahrnbom, Martin ; Jensen, Morten Bornø ; Åström, Kalle ; Nilsson, Mikael ; Ardö, Håkan ; Moeslund, Thomas B. / Improving a real-time object detector with compact temporal information. 2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop. IEEE, 2017. s. 190-197 (IEEE International Conference on Computer Vision Workshops (ICCVW)).
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title = "Improving a real-time object detector with compact temporal information",
abstract = "Neural networks designed for real-time object detection have recently improved significantly, but in practice, look- ing at only a single RGB image at the time may not be ideal. For example, when detecting objects in videos, a foreground detection algorithm can be used to obtain compact temporal data, which can be fed into a neural network alongside RGB images. We propose an approach for doing this, based on an existing object detector, that re-uses pretrained weights for the processing of RGB images. The neural network was tested on the VIRAT dataset with annotations for object de- tection, a problem this approach is well suited for. The ac- curacy was found to improve significantly (up to 66{\%}), with a roughly 40{\%} increase in computational time.",
author = "Martin Ahrnbom and Jensen, {Morten Born{\o}} and Kalle {\AA}str{\"o}m and Mikael Nilsson and H{\aa}kan Ard{\"o} and Moeslund, {Thomas B.}",
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Ahrnbom, M, Jensen, MB, Åström, K, Nilsson, M, Ardö, H & Moeslund, TB 2017, Improving a real-time object detector with compact temporal information. i 2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop. IEEE, IEEE International Conference on Computer Vision Workshops (ICCVW), s. 190-197, 2017 IEEE International Conference on Computer Vision Workshop (ICCVW), Venice, Italien, 22/10/2017. https://doi.org/10.1109/ICCVW.2017.31

Improving a real-time object detector with compact temporal information. / Ahrnbom, Martin; Jensen, Morten Bornø; Åström, Kalle; Nilsson, Mikael; Ardö, Håkan; Moeslund, Thomas B.

2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop. IEEE, 2017. s. 190-197 (IEEE International Conference on Computer Vision Workshops (ICCVW)).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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Ahrnbom M, Jensen MB, Åström K, Nilsson M, Ardö H, Moeslund TB. Improving a real-time object detector with compact temporal information. I 2017 IEEE International Conference on Computer Vision Workshop (ICCVW): Computer Vision for Road Scene Understanding and Autonomous Driving workshop. IEEE. 2017. s. 190-197. (IEEE International Conference on Computer Vision Workshops (ICCVW)). https://doi.org/10.1109/ICCVW.2017.31