A methodology for improving the robustness of target tracking algorithms for forward looking infrared (FLIR) imagery is presented. The designed technique exploits a motion prediction metric to identify the occurrence of false alarms and to control the activation of a template matching (TM) based phase. The proposed approach is particularly suited to high speed algorithms in which tracking is generally performed by using a computationally efficient target detection (TD) step and TM only acts as a recovery means. In such frameworks, the activation strategy has a strong impact on tracking performance, as an improper activation pattern could both affect execution speed and result into critical tracking failures. The designed strategy is compared with a reference implementation relying on a distance-based activation logic, showing improved performance and self-adaptability to variations both in image sequence and target characteristics, which would be required in most high speed automatic target tracking scenarios.
Improving Robustness of Infrared Target Tracking Algorithms Based on Template Matching
IEEE Transactions on Aerospace and Electronic Systems ; 47 , 2 ; 1467-1480
2011-04-01
3757539 byte
Article (Journal)
Electronic Resource
English
Target Tracking with Bayesian Fusion Based Template Matching
British Library Conference Proceedings | 2005
|Feature Selection for Reliable Tracking Using Template Matching
British Library Conference Proceedings | 2003
|Efficient Algorithms for Image Template and Dictionary Matching
British Library Online Contents | 2000
|