Object detection and tracking method of AUV based on acoustic vision
Object detection and tracking method of AUV based on acoustic vision
复制标题
基于声视觉的AUV目标检测与跟踪方法
DOI：
10.1007/s13344-012-0047-8
复制
发表时间：
2012-10
影响因子：
1.6
通讯作者：
Xu Yu-ru
中科院分区：
文献类型：
--
作者：
Zhang Tie-dong;Wan Lei;Zeng Wen-jing;Xu Yu-ru
本文提出了一种新的AUV目标检测与跟踪框架，包括水声数据插值、水声图像分割和水下目标跟踪。将该框架应用于基于前视声纳传感器的AUV视觉定位方法的设计中。首先对实时数据流（水声图像）进行预处理，形成完整的水声图像，并提取和确定目标的相关位置信息。针对传统方法中阈值不能自适应调整的问题，提出了一种改进的双阈值分割方法。其次，根据高斯粒子滤波器创建区域信息的表示。提出了结合面积和不变矩的加权融合策略，完善了粒子权值，增强了跟踪鲁棒性。给出了在AUV的真实的声视觉平台上进行海试的结果并进行了讨论。实验结果表明，该方法能够对水下运动目标进行在线检测和跟踪，具有较好的鲁棒性和有效性。
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.
登录
查看更多内容
DOI：
--
发表时间：
2006
期刊：
Caai Transactions on Intelligent Systems
影响因子：
--
作者：
Yushan Sun
通讯作者：
Yushan Sun
影响因子：
4.1
作者：
S. Perry;Ling Guan
通讯作者：
S. Perry;Ling Guan
DOI：
10.1109/icarcv.2004.1468865
发表时间：
2004-12
期刊：
ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004.
影响因子：
--
作者：
B. Kalyan;Arjuna Balasuriya;T. Ura;W. S. Wijesoma
通讯作者：
B. Kalyan;Arjuna Balasuriya;T. Ura;W. S. Wijesoma
DOI：
10.1049/ic:20060567
发表时间：
2006-03
期刊：
--
影响因子：
--
作者：
Daniel E. Clark;Lourdes Ruiz;Y. Pétillot;J. Bell
通讯作者：
Daniel E. Clark;Lourdes Ruiz;Y. Pétillot;J. Bell
影响因子：
4.1
作者：
M. Chantler;J. Stoner
通讯作者：
M. Chantler;J. Stoner