Automated Light Composting with Rendered Images

Lighting is a key element in photography. Professional photographers often work with complex lighting setups to directly capture an image close to the targeted one. Some photographers reversed this traditional workflow. Indeed, they capture the scene under several lighting conditions, then combine the captured images to get the expected one. Acquiring such a set of images is a tedious task and combining them requires some skill in photography. We propose a fully automatic method, that renders, based on a 3D reconstructed model (shape and albedo), a set of images corresponding to several lighting conditions. The resulting images are combined using a genetic optimization algorithm to match the desired lighting provided by the user as an image.