Camera Localisation using Deep Learning for Free View-point Video Applications 

Proposed by Konstantinos Amplianitis

Summary: Free view-point video (FVV) is a system for viewing an event or a performance, allowing the user to freely interact with the object in question by controlling the viewpoint and generating new views of dynamic scene from any known 3D position. For casual FVV applications (i.e, capturing a Juggler with your mobile devices), where the cameras are not static but rather hand-held, the position of the cameras used to reconstruct the object but also the background scene is crucial within the FVV pipeline. The goal of this master thesis is to apply deep learning for learning the visual representation of the scene and predict the position of the cameras within the scene (indoor and outdoor scenarios). The student should evaluate the predicted camera positions using existing structure-from-motion algorithms and propose potential improvements.

Resources: http://mi.eng.cam.ac.uk/projects/relocalisation/#dataset