Bounding Box Dataset Augmentation for Long-range Object Distance Estimation
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021)（2021）
Abstract
Autonomous long-range obstacle detection and distance estimation plays an important role in numerous applications such as railway applications when it comes to locomotive drivers support or developments towards driverless trains. To overcome the problem of small training datasets, this paper presents two data augmentation methods for training the ANN DisNet to perform reliable long-range distance estimation.
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Key words
bounding box dataset augmentation,long-range object distance estimation,railway applications,locomotive drivers support,autonomous long-range obstacle detection,driverless train,ANN DisNet training
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