Object Shape and Reflectance Modeling from a Sparse Set of Images

  • SHEN Li
    Graduate School of Information Science and Technology, Osaka University
  • MACHIDA Takashi
    Graduate School of Information Science and Technology, Osaka University Cybermedia Center, Osaka University
  • TAKEMURA Haruo
    Graduate School of Information Science and Technology, Osaka University

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Description

We propose a photometric method that simultaneously estimates the surface reflectance and geometry properties from four images. In an iterative framework, the specular reflectance is estimated with a reflectance recovery algorithm which uses the data all over the object, and addresses the problem of data inadequacy. Using the result of the specular reflectance recovery, a Photometric Stereo procedure is applied to estimate the local surface parameters at local points. Our approach integrates reflectance recovery and the photometric stereo technique to yield accurate separation, reflectance and surface orientation as demonstrated by our results on synthetic and real images.

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