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Journal Article
Detection of Centerline Crossing in Abnormal Driving using CapsNet
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- Authors
- Minjong Kim, Suyoung Chi
- Issue Date
- 2019-01
- Citation
- Journal of Supercomputing, v.75, no.1, pp.189-196
- ISSN
- 0920-8542
- Publisher
- Springer
- Language
- English
- Type
- Journal Article
- 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.
- KSP Keywords
- CNN model, Creative Commons, Traffic accident