The field of view of a traditional camera has a fixed shape, which limits how we compose scene elements into an image. We present a novel imaging system with a flexible field of view - the size and shape of the field of view can be varied to achieve the desired scene composition.
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A picture taken by a conventional camera captures the scene from the camera's single viewpoint. In many applications in computer vision and computer graphics, it is desirable to capture the scene from a large number of viewpoints. In this project, we explore a class of imaging systems, called radial imaging systems, that capture a scene from circular loci of virtual viewpoints, in addition to the viewpoint of the camera. We have analyzed the structure of the viewpoint locus, the field of view and the resolution characteristics for this class of imaging systems. We have built radial imaging systems that can, from a single image, recover the frontal 3D structure of an object, generate the complete texture map of a convex object, and estimate the parameters of an analytic BRDF for an isotropic material. In addition, one of our systems can recover the complete geometry of a convex object by capturing only two images.
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