Open AccessSurvey of Object Tracking Algorithm Based on Siamese Network
Author(s) -
Mengle Zuo,
Xuyang Zhu,
Yongchao Chen,
Junyang Yu
Publication year - 2022
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 - 10.1088/1742-6596/2203/1/012035
Subject(s) - tracking (education) , artificial intelligence , computer science , video tracking , computer vision , object (grammar) , eye tracking , deep learning , process (computing) , field (mathematics) , algorithm , mathematics , psychology , pedagogy , pure mathematics , operating system
The network model using deep learning have been widely used in the sphereof visual object tracking for the past few years. The Siamese network can utilize the model based on deep learning to achieve a balance between the tracking accuracy and speed in the visual object tracking. This work mainly introduces the development process of the visual target tracking field and traditional target tracking algorithms. It focuses on the Siamese network structure and the improved the Siamese algorithm, and compares tracking results of related algorithms. Aiming at the deficiencies of existing Siamese object tracking algorithms, the future development trend is prospected.