Abstract

Due to the complexity of the shape-from-shading problem, most solutions rely on idealistic conditions. Orthographic imaging, a known distant point light source, and known surface reflectance properties are usually assumed. Furthermore, most real surfaces are neither perfectly diffuse (Lambertian) nor ideally specular (mirror-like); however most shape-from-shading algorithms assume Lambertian reflectance. The behavior of shape-from-shading algorithms that rely on idealistic conditions is unpredictable in real imaging situations. In this paper, the LIRAS (LIght, Reflectance, And Shape) Recovery System is proposed. LIRAS is a practical approach to the shape-from-shading problem, as many of these assumptions are relaxed. LIRAS is also a modular system: there is a component that recovers the surface reflectance properties, thus the assumption of Lambertian reflectance is relaxed. Rather than assume a known illuminant direction, a component exists that can recover the light orientation. Once the reflectance map is determined, another LIRAS module can use this information to recover the shape for non-Lambertian surfaces. Each of these modules is described and a discussion of how the components cooperate to recover three-dimensional shape information in real environments is given. Extensive experimental evaluation is conducted using both synthetic and real images and the results are very encouraging. The contributions of this paper include the design and implementation of LIRAS and the extensive quantative and qualitative experimental results, which can provide guidelines for future refinements of other shape recovery systems.

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