为了改进增强现实实时跟踪系统,评估增强现实特征匹配算子随机树的性能,并与尺度不变特征变换算子SIFT进行比较.分别在旋转变换、尺度变换和光照变换的情况下,测试两种算子的鲁棒性能和匹配速度.实验结果表明,随机树算子能达到每秒30帧的实时特征匹配速度,且光照变换可以到达50%以上的匹配率,但匹配精度有待提高.
In order to improve the augmented reality systems, is presented an evaluation of the randomized tree algorithm for augmented reality feature matching, and compared it with the scale-invariant feature transform algorithm. Tests including the adaptability and matching speed on rotation, scale and illumination changes were carried out. Experimental results showed that random tree can achieve 30 frames per second of real-time feature matching, and moreover, can reach more than 50% of the matching rate when illumination changes, however its matching accuracy still needs to be improved.