Relevance-Based Template Matching for Tracking Targets in FLIR Imagery

被引:9
作者
Paravati, Gianluca [1 ]
Esposito, Stefano [1 ]
机构
[1] Politecn Torino, Dipartimento Automat & Informat, I-10129 Turin, Italy
来源
SENSORS | 2014年 / 14卷 / 08期
关键词
target tracking; infrared sensors; forward-looking infrared images; template matching; OBJECT TRACKING; SEQUENCES; FUSION;
D O I
10.3390/s140814106
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
One of the main challenges in automatic target tracking applications is represented by the need to maintain a low computational footprint, especially when dealing with real-time scenarios and the limited resources of embedded environments. In this context, significant results can be obtained by using forward-looking infrared sensors capable of providing distinctive features for targets of interest. In fact, due to their nature, forward-looking infrared (FLIR) images lend themselves to being used with extremely small footprint techniques based on the extraction of target intensity profiles. This work proposes a method for increasing the computational efficiency of template-based target tracking algorithms. In particular, the speed of the algorithm is improved by using a dynamic threshold that narrows the number of computations, thus reducing both execution time and resources usage. The proposed approach has been tested on several datasets, and it has been compared to several target tracking techniques. Gathered results, both in terms of theoretical analysis and experimental data, showed that the proposed approach is able to achieve the same robustness of reference algorithms by reducing the number of operations needed and the processing time.
引用
收藏
页码:14106 / 14130
页数:25
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