PlugAndFilter: Architecture Agnostic Booster for Lightweight Registration

Abstract

This paper introduces PlugAndFilter, a framework designed to enhance the performance of multi-modal image registration, particularly for real-time video registration tasks. The improvements provided by PlugAndFilter include not only better registration quality for individual image pairs but also the transformation of the image registration methods into a more robust video registration system. These enhancements are made possible by three proposed contributions: Spatial and Temporal outlier detection, along with Confidence-based keypoint accumulation. PlugAndFilter is compatible with a wide range of thermal-visible registration models, and any registration method capable of producing keypoint matches can be integrated. The proposed implementation is optimized for real-time video registration on edge devices, with key design decisions highlighted to support this goal.