Real-time object motion estimation based on frequency domain matching from a single camera

Abstract

In this paper, we propose a new method for estimating motions of a moving object in image sequences from a single camera. Log-polar transform and phase correlation matching method is applied to estimate rotation and scale change between the object in the template image and the object in the next frames. Kalman filtering is utilized to smooth high frequency variation of the estimated rotation and scale motions. Translation of the object is estimated through template matching by dynamically updating template for each frame. Based on the proposed method, we implemented experiments to check accuracy of results from phase correlation matching and demonstrated an application for tracking object motion in real-time image sequences.