Line-Based Multi-Label Energy Optimization for Fisheye Image Rectification and Calibration

Mi Zhang, Jian Yao, Menghan Xia, Kai Li, Yi Zhang, Yaping Liu

Abstract:

Fisheye image rectification and estimation of intrinsic
parameters for real scenes have been addressed in the literature
by using line information on the distorted images.
In this paper, we propose an easily implemented fisheye image
rectification algorithm with line constrains in the undistorted
perspective image plane. A novel Multi-Label Energy
Optimization (MLEO) method is adopted to merge short
circular arcs sharing the same or the approximately same
circular parameters and select long circular arcs for camera
rectification. Further we propose an efficient method to
estimate intrinsic parameters of the fisheye camera by automatically
selecting three properly arranged long circular
arcs from previously obtained circular arcs in the calibration
procedure. Experimental results on a number of real
images and simulated data show that the proposed method
can achieve good results and outperforms the existing approaches
and the commercial software in most cases