首页|Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network

Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network

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In order to solve the problem of small object size and low detection accuracy under the unmanned aerial vehicle(UAV)platform,the object detection algorithm based on deep aggregation network and high-resolution fusion module is studied.Furthermore,a joint network of object detection and feature extraction is studied to construct a real-time multi-object tracking algorithm.For the problem of object association failure caused by UAV movement,image registration is applied to multi-object tracking and a camera motion discrimination model is proposed to improve the speed of the multi-object tracking algorithm.The simulation results show that the algorithm proposed in this study can improve the accuracy of multi-object tracking under the UAV platform,and effectively solve the problem of association failure caused by UAV movement.

moving unmanned aerial vehicle(UAV)platformsmall objectfeature extractionimage registrationmulti-object tracking

刘增敏、王申涛、姚莉秀、蔡云泽

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Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China

Key Laboratory of System Control and Information Processing of Ministry of Education,Shanghai 200240,China

Shanghai Engineering Research Center of Intelligent Control and Management,Shanghai 200240,China

Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education,Shanghai Jiao Tong University,Shanghai 200240,China

Institute of Marine Equipment,Shanghai Jiao Tong University,Shanghai 200240,China

JD Business Growth Department,Beijing 100176,China

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National Natural Science Foundation of ChinaNational science and Technology Major Program of ChinaNational Defense science and Technology Outstanding Youth Science Foundation

616278102018YFB13050032017-JCJQ-ZQ-031

2024

10.1007/s12204-022-2540-4

上海交通大学学报(英文版)
上海交通大学

上海交通大学学报(英文版)

影响因子：0.151
ISSN：1007-1172
年,卷(期)：2024.29(3)