A key challenge in computer vision is to infer object appearance, which is a combination of geometric shape and radiometric properties. Acquisition of geometric shape has been researched extensively over decades, and we have reached a point where several commercial solutions are available for scanning 3D geometry. With systems available for acquiring shape, the next natural step is to acquire radiometric properties from observing light-material interaction. A particular challenge in this endeavor is the decoupling of incident illumination and intrinsic material properties. This decoupling is necessary for inferring material properties and for simulating object appearance in an arbitrary illumination environment.<\/p>\n
\nThe topics to be covered in our workshop will be centered around methods for\u00a0formulating<\/strong>,\u00a0capturing<\/strong>,\u00a0validating<\/strong>,\u00a0compressing<\/strong>, and\u00a0applying\u00a0<\/strong>data-driven BxDF models, and especially their use within the field of computer vision.<\/p>\n