1. Deep-Sea Organisms Tracking Using Dehazing and Deep Learning.
- Author
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Lu, Huimin, Uemura, Tomoki, Wang, Dong, Zhu, Jihua, Huang, Zi, and Kim, Hyoungseop
- Subjects
- *
AUTOMATIC tracking , *DEEP learning , *REMOTE submersibles , *TURBIDITY , *SQUIDS , *SHARKS , *HAZE - Abstract
Deep-sea organism automatic tracking has rarely been studied because of a lack of training data. However, it is extremely important for underwater robots to recognize and to predict the behavior of organisms. In this paper, we first develop a method for underwater real-time recognition and tracking of multi-objects, which we call "You Only Look Once: YOLO". This method provides us with a very fast and accurate tracker. At first, we remove the haze, which is caused by the turbidity of the water from a captured image. After that, we apply YOLO to allow recognition and tracking of marine organisms, which include shrimp, squid, crab and shark. The experiments demonstrate that our developed system shows satisfactory performance. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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