Open AccessResearch and Application of Target Tracking Algorithm in Ship Safety
Author(s) -
Bailin Lin,
Xiao Zhang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1267/1/012057
Subject(s) - particle filter , mean shift , tracking (education) , computer science , computer vision , sequence (biology) , algorithm , filter (signal processing) , research object , scale (ratio) , object (grammar) , polynomial , time complexity , artificial intelligence , video tracking , image (mathematics) , real time computing , mathematics , pattern recognition (psychology) , geography , psychology , pedagogy , mathematical analysis , cartography , regional science , biology , genetics
Target tracking is often used in tasks such as video surveillance. Its purpose is to obtain the target of interest in the sequence image accurately, robustly and in real time, and to establish the connection between the moving objects in each image. In recent years, with the continuous development of the global shipping economy, ships have gradually developed into large-scale and high-speed, and how to ensure the safety of ships sailing in these sports has become an important issue. Based on the principle of particle filter and mean shift algorithm, this paper takes the moving ship as the research object and uses the polynomial fitting method to analyse the performance of the two algorithms. A large number of experimental results show that the mean shift algorithm has higher accuracy, and the particle filter method has better real-time performance. And as the number of particles increases, the accuracy of particle filtering will gradually increase.