Augmented Reality application: A new implementation chain

摘要

Augmented Reality (AR) is a live view of a real-world environment. With advanced AR technology, artificial information about the environment and its objects can be overlaid on the real world. This paper presents a complete augmented reality process for a video sequence captured by a moving camera. The main goal is to construct a full chain composed of 4 blocks that correspond to the main steps of augmented reality process: feature detection, feature extraction, feature matching and image registration. Our work proposes an improved technique for image augmentation, starting from feature detection and ending by image registration. We used the well-known techniques (e.g. SIFT, SURF, etc.) for features detection and extraction in order to compare their performance. Furthermore, we added a features learning step (using SVM, KNN and SRC) to improve the image registration process. The final full chain uses the best method in each block. This best combination is then applied on all video frames taken by the camera. Thereafter, we obtain a video showing the augmented object instead of the real one.