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11 March 2022 Current status and development trend of target tracking methods based on deep learning
Shilin Zhang
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Proceedings Volume 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021); 1216022 (2022) https://doi.org/10.1117/12.2627619
Event: International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 2021, Sanya, China
Abstract
Target tracking is a technology that uses video or image sequence information to predict the motion state and position of a target through modeling. It is a critical basic problem of computer vision, with important theoretical research significance, and has a wide range of applications in autonomous driving, UAV navigation, video surveillance and other aspects. In recent years, with the continuous improvement of hardware facilities and the emergence of deep learning methods, target tracking technology has been rapidly developed. This paper first reviews the previous target tracking methods, and points out that deep learning provides new opportunities for the research of target tracking, then introduces the current target tracking method based on deep learning and explains its working mechanism in depth. After that, this article establishes the evaluation criteria suitable for deep learning target tracking. Finally, it analyzes the problems of deep learning methods in target tracking, and makes a prospect for the future development direction.
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Shilin Zhang "Current status and development trend of target tracking methods based on deep learning", Proc. SPIE 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 1216022 (11 March 2022); https://doi.org/10.1117/12.2627619
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KEYWORDS
Detection and tracking algorithms
Optical tracking
Convolutional neural networks
Evolutionary algorithms
Neural networks
Video
Video surveillance
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