Improved Multi-object Tracking Algorithm for Forward Looking Sonar Based on Rotation Estimation

2019 ◽  
pp. 171-183
Author(s):  
Xiufen Ye ◽  
Xinglong Ma
Keyword(s):  
Object Tracking ◽  
Tracking Algorithm ◽  
Rotation Estimation ◽  
Forward Looking

scholarly journals Robust long-term object tracking with adaptive scale and rotation estimation

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142090973
Author(s):  
Huimin Lu ◽  
Dan Xiong ◽  
Junhao Xiao ◽  
Zhiqiang Zheng
Keyword(s):  
Object Tracking ◽  
Estimation Method ◽  
Tracking Algorithm ◽  
Correlation Filter ◽  
Estimation Accuracy ◽  
Continuous Space ◽  
Searching Method ◽  
Object Searching ◽  
Rotation Estimation

In this article, a robust long-term object tracking algorithm is proposed. It can tackle the challenges of scale and rotation changes during the long-term object tracking for security robots. Firstly, a robust scale and rotation estimation method is proposed to deal with scale changes and rotation motion of the object. It is based on the Fourier–Mellin transform and the kernelized correlation filter. The object’s scale and rotation can be estimated in the continuous space, and the kernelized correlation filter is used to improve the estimation accuracy and robustness. Then a weighted object searching method based on the histogram and the variance is introduced to handle the problem that trackers may fail in the long-term object tracking (due to semi-occlusion or full occlusion). When the tracked object is lost, the object can be relocated in the whole image using the searching method, so the tracker can be recovered from failures. Moreover, two other kernelized correlation filters are learned to estimate the object’s translation and the confidence of tracking results, respectively. The estimated confidence is more accurate and robust using the dedicatedly designed kernelized correlation filter, which is employed to activate the weighted object searching module, and helps to determine whether the searching windows contain objects. We compare the proposed algorithm with state-of-the-art tracking algorithms on the online object tracking benchmark. The experimental results validate the effectiveness and superiority of our tracking algorithm.

High speed long-term visual object tracking algorithm for real robot systems

2021 ◽  
Vol 434 ◽  
pp. 268-284
Author(s):  
Muxi Jiang ◽  
Rui Li ◽  
Qisheng Liu ◽  
Yingjing Shi ◽  
Esteban Tlelo-Cuautle
Keyword(s):  
Object Tracking ◽  
High Speed ◽  
Tracking Algorithm ◽  
Visual Object ◽  
Visual Object Tracking ◽  
Robot Systems ◽  
Real Robot

Siamese single object tracking algorithm with natural language prior

2021 ◽  
Vol 15 (5) ◽  
Author(s):  
Qianli Zhou ◽  
Rong Wang ◽  
Jinze Li ◽  
Naiqian Tian ◽  
Wenjin Zhang
Keyword(s):  
Natural Language ◽  
Object Tracking ◽  
Tracking Algorithm ◽  
Single Object

Design of UAV Single Object Tracking Algorithm Based on Feature Fusion

2021 ◽  
Author(s):  
Changze Li ◽  
Xiaoxiong Liu ◽  
Xingwang Zhang ◽  
Bin Qin
Keyword(s):  
Object Tracking ◽  
Feature Fusion ◽  
Tracking Algorithm ◽  
Single Object
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