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The Journal of Supercomputing

Erschienen in:

19.06.2018

Detection of centerline crossing in abnormal driving using CapsNet

verfasst von: Minjong Kim, Suyoung Chi

Erschienen in: The Journal of Supercomputing | Ausgabe 1/2019

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Abstract

This paper presents the detection of centerline crossing in abnormal driving using a CapsNet. The benefit of the CapsNet is that the capsule contains all the data about the status of objects and recognizes objects as vectors; hence, these can be used to classify driving as normal or abnormal. The datasets use the Creative Commons Licenses from YouTube to obtain traffic accident footages and six time-flow images composed of data with our quantitative basis. A comparison of our proposed architecture with the CNN model showed that our method produces better results.

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Titel: Detection of centerline crossing in abnormal driving using CapsNet
verfasst von: Minjong Kim
Suyoung Chi
Publikationsdatum: 19.06.2018
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 1/2019
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-018-2459-6

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