红外技术Issue(12)：780-787,8.
基于TLD的舰船目标跟踪方法研究
Ship Target Tracking Based on Tracking-Learning-Detecting Tactics
摘要
Abstract
When warship targets are tracked in complex background, the targets loss may occur in some frames. In order to overcome the problem, a tracking-learning-detecting(TLD)algorithm is introduced. With the random ferns classifier which is trained online, the detection is performed based on the classification results. PN learning constrained by spatial and temporal features is used to update the classifier. The detection results and tracking results are fused to locate the target in each frame. Finally, experimental result shows that the TLD tracking algorithm has a high recognition rate and a low false detection rate. Benefitting from continuous learning with various target changes in each frame, the TLD algorithm is robust to target appearance changes and occlusion, and has a good real-time performance. The proposed algorithm can meet the requirements of general online tracking system.关键词
舰船跟踪/随机蕨分类器/TLD算法/在线学习Key words
ship tracking/random ferns classifier/TLD algorithm/online learning分类
信息技术与安全科学引用本文复制引用
齐楠楠,揭斐然,谢熙,吴巍..基于TLD的舰船目标跟踪方法研究[J].红外技术,2013,(12):780-787,8.基金项目
国家自然科学基金资助项目，编号61273241；航空科学基金，编号20105179002。 （）
