Abstract: A computer vision method for generating a three dimensional reconstruction of an object, the method comprising: receiving a set of photometric stereo images of the object, the set of photometric stereo images comprising a plurality of images using illumination from different directions using one or more light sources; using a trained neural network to generate a normal map of the object; and producing a 3D reconstruction of said object from said normal map, wherein using said trained neural network comprises converting said set of photometric stereo images to an input form suitable for an input layer of said neural network, wherein said input form comprises, for each pixel, a representation of the different lighting directions and their corresponding intensities which have been obtained from photometric stereo images to which a compensation has been applied, the compensation being determined from an estimate of the distance between the lighting source and a point on the object to which the pixel correspond

Abstract: A system for producing a 3D image of an object, the system includes: a processor adapted to receive multiview stereo photometric data, the multiview photometric stereo data including a first set of image data, wherein the first set of image data includes images captured by the first camera at a plurality of positions with illumination from different illumination directions such that there are a plurality of images from a different illumination direction for each position of the first camera, the processor being adapted to process the multiview photometric stereo data using a photometric stereo approach with a formulation of the irradiance using a reflection model that models both diffuse and specular reflection.

Abstract: A computer vision method for generating a three dimensional reconstruction of an object, the method comprising: receiving a set of photometric stereo images of the object, the set of photometric stereo images comprising a plurality of images using illumination from different directions using one or more light sources; using a trained neural network to generate a normal map of the object; and producing a 3D reconstruction of said object from said normal map, wherein using said trained neural network comprises converting said set of photometric stereo images to an input form suitable for an input layer of said neural network, wherein said input form comprises, for each pixel, a representation of the different lighting directions and their corresponding intensities which have been obtained from photometric stereo images to which a compensation has been applied, the compensation being determined from an estimate of the distance between the lighting source and a point on the object to which the pixel correspond

Abstract: A system for producing a 3D image of an object, the system includes: a processor adapted to receive multiview stereo photometric data, the multiview photometric stereo data including a first set of image data, wherein the first set of image data includes images captured by the first camera at a plurality of positions with illumination from different illumination directions such that there are a plurality of images from a different illumination direction for each position of the first camera, the processor being adapted to process the multiview photometric stereo data using a photometric stereo approach with a formulation of the irradiance using a reflection model that models both diffuse and specular reflection.