标题：
Visual Tracking Algorithm for Aircrafts in Airport
点击次数：
所属单位：
理学院
发表刊物：
Proc. - Int. Symp. Comput. Intell. Des., ISCID
摘要：
Visual tracking for aircraft is an important part of the airport surface surveillance. However, the current tracking algorithms do not perform well in complex environment like the airport. Aiming at this problem, this paper proposes a target tracking algorithm based on the correlation filter using deep conventional feature. Firstly, a convolution neural network is trained for the classification of aircraft. Then the shallow and deep features of the target are extracted by the network. Finally, these features are fused into the correlation filter tracking method. The proposed algorithm is compared with other trackers on ten video sequences with different weather conditions and different locations in the airport. Experimental results show that the proposed method can achieve high accuracy and success rate, and the overall performance is superior to other comparative algorithms. © 2018 IEEE.
是否译文：
否
发表时间：
2018-07-02
合写作者：
丁萌,Wang, Wei
通讯作者：
张旭
发表时间：
2018-07-02
学位：理学博士学位
职称：讲师
所在单位：理学院