Apart from forensic experts, ordinary users can benefit from geo-localization as well – for example to edit their holiday pictures. Computational photography offers a wide range of uses in editing existing pictures. “The user can simulate a different camera and refocus an existing picture. Information on the distance of a mountain peak can be used to artificially refocus the picture in a way our equipment would never permit. We can see, how a picture would look like if we would take it with a large telescope,” said Cadik, a former Max Planck Institute post-doc, presenting a possible application of his research.

“A picture dimmed with mist can be easily and automatically brightened and skies cleared. On the other hand, a mist can be easily added for an artistic impression. Nowadays, this is a difficult task to be done manually, we know how to achieve this automatically,” said Cadik, who claims that computational photography brings a new approach to editing pictures. It is possible to change the lighting of a picture, add artificial shadows made by the terrain features and edit the picture to look as if it was taken during sunrise or sunset. “Nowadays, it is increasingly difficult to recognize an edited, artificially altered picture. However, it is possible. That is the focus of our work in forensic picture analysis,” added IT researcher from Brno.

A connection of information from a picture and 3D terrain models help users gain more data on surrounding landscape, such as names of nearby mountains, distances and altitudes of their peaks. Geo-localization of pictures could also be utilised by Swiss Alpine Rescue service that uses extensive camera network to monitor snow cover. An extension of data from digital 3D models could provide rescuers valuable additional information on the surrounding landscape.

Information on landscape is also helpful with navigating self-driving cars and drones. Martin Cadik´s team focuses on geo-localization of landscape pictures, however they can also analyse photos and videos taken in cities as well. In such cases, they compare a picture with an existing database, such as Google Street View. With landscape models, the researchers use digital 3D models enhanced by data from a public geographical database Open Street Map. Geo-localization is also relevant in the design of autonomous space rovers used in Mars exploration, that also use surrounding landscape features for navigation.