Detection of centerline crossing in abnormal driving using CapsNet
| Autor: | Minjong Kim, Suyoung Chi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
020203 distributed computing
Basis (linear algebra) Hardware and Architecture Computer science business.industry 0202 electrical engineering electronic engineering information engineering Computer vision 02 engineering and technology Artificial intelligence business Software Information Systems Theoretical Computer Science |
| Zdroj: | The Journal of Supercomputing. 75:189-196 |
| ISSN: | 1573-0484 0920-8542 |
| DOI: | 10.1007/s11227-018-2459-6 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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