Abstract: A method is described which included receiving (S1) a number of object images (IMn) of an object (1). Each object image (IMn) corresponds to a different view direction (n). The object images include first (IM1) and second (IM2) object images corresponding to first (n1) and second (n2) directions. The method also includes determining (S2) a mesh (20) corresponding to the target region (5) of the object (1) surface (2) based on a first subset (MESH) of the number of object images (IMn) which includes two or more object images (IMn) of the number of object images (IMn). The method also includes determining (S3) diffuse (DFUV) and specular (SPUV) maps corresponding to the target region (5) of the object (1) surface (2) based on processing a second subset (REFLECT) of the object images (IMn) using a deep learning neural network model trained to estimate diffuse (DFn) and specular (SPn) albedo components based on an input image (IMn).

Abstract: An apparatus (1, 5, 6) is described which includes two or more colour displays (2) arranged to provide piece-wise continuous illumination of a volume. The apparatus (1, 5, 6) also includes one or more cameras (3). Each camera (3) is arranged to image the volume. The apparatus (1, 5, 6) is configured to control the two or more colour displays (2) and the one or more cameras (3) to illuminate the volume with each of two or more illumination conditions. The apparatus (1, 5, 6) is also configured to obtain two or more sets of images. Each set of images is obtained during illumination of the volume with one or more corresponding illumination conditions. The two or more sets of images include sufficient information for calculation of a reflectance map and a photometric normal map of an object or subject (4) positioned within the volume. When viewed from the volume, the apparatus (1, 5, 6) only provides direct illumination of the volume from angles within a zone of a hemisphere.