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Underwater Object Detection and Pose Estimation using Deep Learning
- Authors
- Jeon, M.; Lee, Y.; Shin, Y.-S.; Jang, H.; Kim, A.
- Issue Date
- 2019
- Publisher
- Elsevier B.V.
- Citation
- IFAC-PapersOnLine, v.52, no.21, pp 78 - 81
- Pages
- 4
- Journal Title
- IFAC-PapersOnLine
- Volume
- 52
- Number
- 21
- Start Page
- 78
- End Page
- 81
- ISSN
- 2405-8963
- Abstract
- This paper presents an approach for making a dataset using a 3D CAD model for deep learning based underwater object detection and pose estimation. We also introduce a simple pose estimation network for underwater objects. In the experiment, we show that object detection and pose estimation networks trained via our synthetic dataset present a preliminary potential for deep learning based approaches in underwater. Lastly, we show that our synthetic image dataset provides meaningful performance for deep learning models in underwater environments. ？ 2019. The Authors. Published by Elsevier Ltd. All rights reserved.
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