Feature-based Recursive Observer Design for Homography Estimation
This addresses real-time homography estimation for robotic vehicles, but it appears incremental as it builds on existing group structure and sensor fusion methods.
The paper tackles the problem of online homography estimation for robotic vision by developing a recursive observer that uses the Special Linear group structure, gyroscope data, and point-feature correspondences, achieving robust performance in challenging conditions like fast motion and occlusions.
This paper presents a new algorithm for online estimation of a sequence of homographies applicable to image sequences obtained from robotic vehicles equipped with vision sensors. The approach taken exploits the underlying Special Linear group structure of the set of homographies along with gyroscope measurements and direct point-feature correspondences between images to develop temporal filter for the homography estimate. Theoretical analysis and experimental results are provided to demonstrate the robustness of the proposed algorithm. The experimental results show excellent performance even in the case of very fast camera motion (relative to frame rate), severe occlusion, and in the presence of specular reflections.