Object Detection and Tracking Method of AUV Based on Acoustic Vision  

作　　者：张铁栋 万磊 曾文静 徐玉如 

机构地区：[1]National Key Laboratory of Science and Technology on Autonomous Underwater Vehicle,Harbin Engineering University

出　　处：《China Ocean Engineering》2012年第4期623-636,共14页中国海洋工程（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.51009040);Heilongjiang Postdoctoral Fund(Grant No.LBH-Z11205);the National High Technology Research and Development Program of China(863 Program,Grant No.2011AA09A106);the China Postdoctoral Science Foundation(Grant No.2012M510928)

摘　　要：This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow （underwater acoustic images） is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow （underwater acoustic images） is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.

关 键 词：AUV acoustic image object detection Gaussian particle filter object tracking 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP391.41[自动化与计算机技术—控制科学与工程]