The traditional augmented reality algorithms for natural image detect and extract the natural features of a template image for multi scales. At the tracking stage the algorithms match the screen features with all of the features extracted from the template image

which produces a large amount of useless computation and reduces the efficiency of feature matching. To solve this problem

this article presents an algorithm which can locate the scale and area of the template image fast and accelerate the speed of 3D tracking. In the preprocess stage

the image in each scale is partitioned into small areas

and the features of the template image are managed according to the scale and area. In the real-time tracking stage

the method locates the scale and area of current camera image quickly using some computation geometry algorithms so that the scope of feature matching is decreased. The search field of feature matching

cuts down the time spent by feature matching

compared with the traditional method

the time spent by feature matching is cut short by about 10 times and the time spent by tracking one frame is cut short by 1.82 times when the resolution of template image is high. The frame rate of the 3d tracking algorithm keeps at 15 frames per second on average. Our method can be used to the tracking of natural image on mobile platform

especially when the resolution of image is high

the method can narrow the search field of image scale and area and promote the efficiency of real-time 3d tracking algorithm.