An Augmented Reality Tracking Registration Method Based on Deep Learning

Abstract

Augmented reality is a three-dimensional visualization technology that can carry out human-computer interaction. Virtual information is placed in the designated area of the real world to enhance real-world information. Based on the existing implementation process of augmented reality, this paper proposes an augmented reality method based on deep learning, aiming at the inaccurate positioning and model drift of the augmented reality method without markers in complex backgrounds, light changes, and partial occlusion. The proposed method uses the lightweight SSD model for target detection, the SURF algorithm to extract feature points and the FLANN algorithm for feature matching. Experimental results show that this method can effectively solve the problems of inaccurate positioning and model drift under particular circumstances while ensuring the operational efficiency of the augmented reality system.