Automatic Estimation of Sphere Centers from Images of Calibrated Cameras
This addresses calibration for robotic vision, specifically in autonomous cars, but appears incremental as it builds on existing methods for ellipse detection and sphere estimation.
The paper tackled the problem of automatically detecting ellipses in camera images and estimating the 3D positions of corresponding spheres for calibration, achieving results tested quantitatively and qualitatively in autonomous car sensor systems.
Calibration of devices with different modalities is a key problem in robotic vision. Regular spatial objects, such as planes, are frequently used for this task. This paper deals with the automatic detection of ellipses in camera images, as well as to estimate the 3D position of the spheres corresponding to the detected 2D ellipses. We propose two novel methods to (i) detect an ellipse in camera images and (ii) estimate the spatial location of the corresponding sphere if its size is known. The algorithms are tested both quantitatively and qualitatively. They are applied for calibrating the sensor system of autonomous cars equipped with digital cameras, depth sensors and LiDAR devices.