Precision in pursuit: a multi-consistency joint approach for infrared anti-UAV tracking

Abstract In addition to addressing the issues commonly encountered in generic visual object tracking, Anti-UAV tracking endeavors necessitates coping with the diminutive characteristics of infrared UAV targets, potential discontinuities of targets between adjacent frames due to irregular motion patterns and camera rotations, and the occurrence of drastic target deformations. To effectively tackle these challenges, we present a multi-consistency joint approach tailored for infrared Anti-UAV tracking. The concept of consistency is realized across three pivotal perspectives: Firstly, by acknowledging the inherent motion consistency of targets, we introduce the Robust Motion Constraint Module (RMCM). This module effectively mitigates tracking drift issues and enhances the precision of local tracking by imposing constraints on the position and size variations of the tracked results through an adaptive cost matrix. Secondly, we design the Flexible Spatial Remapping Module (FSRM) grounded in spatial consistency. This module facilitates the identification of correspondences between images in adjacent frames, effectively resolving the substantial target displacement arising from the relative motion between UAVs and cameras. Lastly, we propose the Adaptive Template Update Strategy (ATUS) to address the challenge of significant target deformations. This strategy dynamically selects alternate templates to ensure feature consistency, thereby maintaining stable tracking even in the face of drastic pose changes. The experimental results on benchmark datasets unequivocally demonstrate that our approach achieves promising advancements compared to state-of-the-art models. We will make our code publicly available upon the acceptance of our paper.