基于SIFT关键点的增强现实初始化算法

介绍了一种基于SIFT关键点的无标志点增强现实初始化算法。算法在已知场景少量标定关键帧图像的基础上，将关键帧图像与当前视频图像帧中的SIFT关键点进行匹配，利用RANSAC算法消除外点，而后利用图像匹配算法获取摄像机的位置和方向信息，完成系统的自动初始化工作。实验结果表明，算法鲁棒性强，跟踪定位精度高，有效地减小了人工干预的工作量。

System initialization algorithm based on SIFT key points for markerless augmented reality applications

System initialization algorithm applied for markedess augmented reality applications based on SIFT key points is presented. A small number of key-frames of the real environment are calibrated in the offline process and used to detect the target object in video frame. During the on-line initialization stage, the target object is automatically detected by matching the SIFT key points extracted on the input image and the selected key-frames. The RANSAC algorithm is employed to further optimize point correspondences and discard outliers. The camera pose is accurately estimated using an image registration algorithm. Experimental results demonstrate that our algorithm is accurate, robust, and can effectively reduce manual work.