| Literature DB >> 31944944 |
Nicola Capece, Francesco Banterle, Paolo Cignoni, Fabio Ganovelli, Ugo Erra, Mike Potel.
Abstract
We introduce a novel algorithm that turns a flash selfie taken with a smartphone into a studio-like photograph with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in a controlled environment. For each pair, we have one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend lighting artifacts introduced by a close-up camera flash, such as specular highlights, shadows, and skin shine.Year: 2020 PMID: 31944944 DOI: 10.1109/MCG.2019.2958274
Source DB: PubMed Journal: IEEE Comput Graph Appl ISSN: 0272-1716 Impact factor: 2.088