Semi-automatic recognition of marine debris on beaches

By Zhenpeng Ge, Huahong Shi, Xue Mei, Z. Dai, Daoji Li. 2016

40 citations recorded by the source corpus.

An increasing amount of anthropogenic marine debris is pervading the earth’s environmental systems, resulting in an enormous threat to living organisms. Additionally, the large amount of marine debris around the world has been investigated mostly through tedious manual methods. Therefore, we propose the use of a new technique, light detection and ranging (LIDAR), for the semi-automatic recognition of marine debris on a beach because of its substantially more efficient role in comparison with other more laborious methods. Our results revealed that LIDAR should be used for the classification of marine debris into plastic, paper, cloth and metal. Additionally, we reconstructed a 3-dimensional model of different types of debris on a beach with a high validity of debris revivification using LIDAR-based individual separation. These findings demonstrate that the availability of this new technique enables detailed observations to be made of debris on a large beach that was previously not possible. It is strongly suggested that LIDAR could be implemented as an appropriate monitoring tool for marine debris by global researchers and governments.

Subfields: Computer Vision and Pattern Recognition, Pollution, Water Science and Technology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Junaed Sattar
2. Michael Fulton
3. Jungseok Hong
4. M. Islam
5. Peigen Luo
6. Peixian Zhuang
7. Chongyi Li

In Pollution

1. Michael Fulton
2. Junaed Sattar
3. Jungseok Hong

In Water Science and Technology

1. Michael Fulton
2. Junaed Sattar
3. Jungseok Hong

Citations in the corpus

• TrashCan: A Semantically-Segmented Dataset towards Visual Detection of Marine Debris (2020, methodology): “cientific inquiry for some time, autonomous detection of trash has been less studied. Researchers have studied at the removal of debris from the ocean surface [5], mapping trash on beaches using LIDAR [6], and using forward-looking sonar (FLS) imagery to detect underwater debris by training a deep co”
• Robotic Detection of Marine Litter Using Deep Visual Detection Models (2018, methodology): “[17] uses LIDAR to find and map trash on beaches.”