In-situ autonomous observation method based on hadal fish recognition

被引：0

作者：

Chen J. ^{[1
,2
]}

Zhang Q.-F. ^{[1
]}

Zhang A.-Q. ^{[1
,3
]}

Cai D.-S. ^{[3
]}

机构：

[1] State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang

[2] University of Chinese Academy of Science, Beijing

[3] Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya

来源：

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2019年 / 49卷 / 03期

关键词：

Autonomous observation; Fish recognition; Hadal fauna; Marine engineering and technology; Support vector machine; Video camera system;

D O I：

10.13229/j.cnki.jdxbgxb20180160

中图分类号：

学科分类号：

摘要：

In-situ observation of hadal fish has been widely implemented for scientific research, usually on serial time or fixed time interval observation mode. However, the observation efficiency is extremely low since pre-programmed method cannot perceive the interested targets in camera view. A novel autonomous observation method combined with computer vision technology is proposed, where observation strategy could be dynamically adjusted according to the result of fish recognition. Moving targets are rapidly segmented from video frames based on improved background difference method. Invariant moment, eccentricity and roundness characteristics are extracted subsequently, and Fisher discriminant function is used for feature reduction. Fish target prediction model is then established with PSO-SVM algorism. The effectiveness of proposed autonomous observation method is validated through simulation experiment using in-situ observation video data of hadal trench expedition. © 2019, Jilin University Press. All right reserved.

引用

页码：953 / 962

页数：9

共 24 条

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