Improving Robustness of Infrared Target Tracking Algorithms Based on Template Matching

Abstract

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.