M.sc Thesis Sift Based Augmented Reality Sift Based Augmented Reality

This study proposes augmented reality as a tool to access Internet information from mobile devices and prototypes for markerless outdoor augmented reality application based on SIFT (Scale Invariant Feature Transform) features are implemented. They comprise a reference data set of SIFT points extracted from images of the square Place des Terreaux in Lyons. These SIFT features are projected on a digital model of the building façades of the square to obtain 3D coordinates for each feature point. The algorithms implemented calculate the camera pose for frame of a video from 3D-2D point correspondences between features extracted in the current video frame and points in the reference dataset. The algorithms were successfully tested on a video film of the square. Although they do not operate in real-time, they are capable of a correct pose estimation and projection of artificial data into the scene. In case of a loss of track, the algorithms recover automatically. The study shows the potential of SIFT features for purely image based markerless outdoor augmented reality applications..