Camera calibration with two arbitrary coaxial circles

We present an approach for camera calibration from the image of at least two circles arranged in a coaxial way. Such a geometric configuration arises in static scenes of objects with rotational symmetry or in scenes including generic objects undergoing rotational motion around a fixed axis. The approach is based on the automatic localization of a surface of revolution (SOR) in the image, and its use as a calibration artifact. The SOR can either be a real object in a static scene, or a “virtual surface” obtained by frame superposition in a rotational sequence. This provides a unified framework for calibration from single images of SORs or from turntable sequences. Both the internal and external calibration parameters (square pixels model) are obtained from two or more imaged cross sections of the SOR, whose apparent contour is also exploited to obtain a better calibration accuracy. Experimental results show that this calibration approach is accurate enough for several vision applications, encompassing 3D realistic model acquisition from single images, and desktop 3D object scanning.