Drift-free motion estimation from video images using phase correlation and linear optimization
Yoshi Ri, Hiroshi Fujimoto · 2018
Motion reconstruction from video images is known as an effective way in the autonomous robot guidance or teaching for a particular task. The authors' goal is to reconstruct motion from a video with the image-based visual servoing, and the main topic of this paper is to estimate camera motion on the image plane to make a reference. This paper focuses on a drift-free robust camera motion estimation by utilizing all relationships between every two frames. The proposed method in this paper does not use feature points like well-known bundle adjustment. It enables us to use a linear equation to solve its optimization. Then, brand new solution by using distance matrix is proposed so that it can save computation time and memory against a common pseudo inverse matrix based method. Finally, both qualitative and quantitative evaluations based on image mosaicing technique were achieved to confirm the effectiveness of proposed method.