Camera calibration and light source orientation from solar shadows

  • Authors:

  • Xiaochun Cao;Hassan Foroosh

  • Affiliations:

  • Computational Imaging Laboratory, University of Central Florida, Orlando, FL 32816-2362, USA;Computational Imaging Laboratory, University of Central Florida, Orlando, FL 32816-2362, USA

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2007

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Abstract

In this paper, we describe a method for recovering camera parameters from perspective views of daylight shadows in a scene, given only minimal geometric information determined from the images. This minimal information consists of two 3D stationary points and their cast shadows on the ground plane. We show that this information captured in two views is sufficient to determine the focal length, the aspect ratio, and the principal point of a pinhole camera with fixed intrinsic parameters. In addition, we are also able to compute the orientation of the light source. Our method is based on exploiting novel inter-image constraints on the image of the absolute conic and the physical properties of solar shadows. Compared to the traditional methods that require images of some precisely machined calibration patterns, our method uses cast shadows by the sun, which are common in natural environments, and requires no measurements of any distance or angle in the 3D world. To demonstrate the accuracy of the proposed algorithm and its utility, we present the results on both synthetic and real images, and apply the method to an image-based rendering problem.