Automatic Calibration of Soccer Scenes Using Feature Detection

Abstract

In this paper, we present a method to calibrate large scale camera networks for multi-camera computer vision applications in soccer scenes. The calibration process determines camera parameters, both within each camera (focal length, principal point, etc.) and inbetween the cameras (their relative position and orientation). We first extract candidate image correspondences over adjacent cameras, without using any calibration object, relying on existing feature matching methods. We then combine these pairwise camera feature matches over all adjacent cameras using a confident-based voting mechanism and a selection relying on the general displacement across the images. Experiments show that this removes a large amount of outliers before using existing calibration toolboxes dedicated to small scale camera networks, that would otherwise fail to work properly in finding the correct camera parameters over large scale camera networks. We succesfully validate our method on real soccer scenes.