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Reconstructing an object's high-quality 3D shape with inherent spectralreflectance property, beyond typical device-dependent RGB albedos, opens thedoor to applications requiring a high-fidelity 3D model in terms of bothgeometry and photometry. In this paper, we propose a novel Multi-View InverseRendering (MVIR) method called Spectral MVIR for jointly reconstructing the 3Dshape and the spectral reflectance for each point of object surfaces frommulti-view images captured using a standard RGB camera and low-cost lightingequipment such as an LED bulb or an LED projector. Our main contributions aretwofold: (i) We present a rendering model that considers both geometric andphotometric principles in the image formation by explicitly considering cameraspectral sensitivity, light's spectral power distribution, and light sourcepositions. (ii) Based on the derived model, we build a cost-optimization MVIRframework for the joint reconstruction of the 3D shape and the per-vertexspectral reflectance while estimating the light source positions and theshadows. Different from most existing spectral-3D acquisition methods, ourmethod does not require expensive special equipment and cumbersome geometriccalibration. Experimental results using both synthetic and real-world datademonstrate that our Spectral MVIR can acquire a high-quality 3D model withaccurate spectral reflectance property.

Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance