Generic Scene Recovery Using Multiple Images

  • Authors:
  • Kuk-Jin Yoon;Emmanuel Prados;Peter Sturm

  • Affiliations:
  • Computer vision Lab., Dept. Information and Communications, GIST, Korea;Perception Lab., INRIA Grenoble - Rhône-Alpes, France;Perception Lab., INRIA Grenoble - Rhône-Alpes, France

  • Venue:
  • SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
  • Year:
  • 2009

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Abstract

We present a generative model based method for recovering both the shape and the reflectance of the surface(s) of a scene from multiple images, assuming that illumination conditions are known in advance. Based on a variational framework and via gradient descents, the algorithm minimizes simultaneously and consistently a global cost functional with respect to both shape and reflectance. Contrary to previous works which consider specific individual scenarios, our method applies to a number of scenarios --- mutiview stereovision, multiview photometric stereo, and multiview shape from shading. In addition, our approach naturally combines stereo, silhouette and shading cues in a single framework and, unlike most previous methods dealing with only Lambertian surfaces, the proposed method considers general dichromatic surfaces.