Landmark Detection Using Machine Learning

As smartphones and mobile data become more prevalent in modern society, the possibilities for them to interact with the physical world also grow exponentially. Technologies such as Oculus Rift and Google Glass are attempting to bridge the gap between the virtual and the physical, and as enhancements in computer speed and image processing are made, the concept of Augmented Reality (AR) becomes more tangible. However, one difficulty with AR is the sheer complexity of image processing and feature recognition. A successful AR system must be able to distinguish among a large number of landmarks and should be able to adapt to the existence of new landmarks. Because of the adaptability requirement, AR algorithms naturally lend themselves to using machine learning. As such, the focus of this project is to develop, refine and document a machine learning algorithm that can distinguish landmarks from images using a database of known landmarks.