Polycameras: Camera Clusters for Wide Angle Imaging

We present the idea of a polycamera which is defined as a tightly packed camera cluster. The cluster is arranged so as to minimize the overlap between adjecent views. The objective of such clusters is to be able to image a very large field of view without loss of resolution. Since these clusters do not have a single viewpoint, analysis is provided on the effects of such non-singularities. We also present certain conbfigurations for polycameras which cover varying fields of view. We would like to minimizze the number of sensors required to capture a given field of view. Therefore we recommend the use of wide-angle sensors as opposed to traditional long focal length sensors. However, such wide-angle sensors tend to have severe distortions which pull points towards the optical center. This paper also proposes a method for recovering the distortion parameters without the use of any calibration objects. Since distortions cause straight lines in the scene to appear as curves in the image, our algorithm seeks to find the distortion parameters that would map the image curves to straight lines. The user selects a small set of points along the image curves. Recovery of the distortion parameters is formulated as the minimization of an objective function which is designed to explicitly account for noise in the selected image points. Experimental results are presented for synthetic data with different noise levels as well as for real images. Once calibrated, the image stream from a wide angle camera can be undistorted in real time using look up tables. Finally, we apply our distortion correction technique to a polycamera made of four wide-angle cameras to create a high resolution 360 degree panorama in real-time. Index Terms — camera calibration, wide-angle lens, radial distortion, decentering distortion, camera clusters, polycamera, single viewpoints constraint, minimum working distance, real-time panoramic sensor.