Tracking registration is a key issue in augmented reality applications,particularly where there are no artificial identifier placed manually.In this paper,an efficient markerless tracking registration algorithm which combines the detector and the tracker is presented for the augmented reality system.We capture the target images in real scenes as template images,use the random ferns classifier for target detection and solve the problem of reinitialization after tracking registration failures due to changes in ambient lighting or occlusion of targets.Once the target has been successfully detected,the pyramid Lucas-Kanade(LK)optical flow tracker is used to track the detected target in real time to solve the problem of slow speed.The least median of squares(LMedS)method is used to adaptively calculate the homography matrix,and then the three-dimensional pose is estimated and the virtual object is rendered and registered.Experimental results demonstrate that the algorithm is more accurate,faster and more robust.
展开▼
