Markerless Tracking Algorithm Based on 3D Model for Augmented Reality System

We present a markerless augmented reality(AR) system based on 3D model. First, the feature of environment was extracted using SIFT operator, then the method of stratified reconstruction was used to reconstruct the 3D scene, after that we constructed the database of prior knowledge using the KD-Tree. Finally, we tracked the 3D model based on these prior knowledge via feature matching and pose estimation in real time. Experimental results demonstrated that this method is sufficient for markerless tracking registration. With the prior knowledge, key frame selection problem can be avoided and the running speed is also increased.

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