Robust Painting Recognition and Registration for Mobile Augmented Reality

In this work we introduce a novel approach for painting recognition and registration for mobile Augmented Reality applications. To address the challenges of real-time painting recognition and registration we introduce three main contributions: i) A relevant painting region detector extracts the painting region from the given image. ii) Two local and global features are extracted from the relevant region to robustly match a painting database. iii) A RANSAC homography estimation method is used to overlay the additional content in an AR framework. Experiments have been carried out on a dataset built with publicly available images.