Application of scene recognition technology based on fast ER and surf algorithm in augmented reality

In consideration of problems with augmented reality, including untimeliness, inaccuracy and instability of spatial registration results, we proposes an improved algorithm based on FAST-ER (Features from Accelerated Segment Test) and SURF (Speeded-Up Robust Features) in this paper, which does not only improve recursive adjustment methods for decision trees during feature point extraction, but also overcome problems of traditional FAST-ER algorithms such as heavy computation load and ineffective feature point extraction. After information about location parameters of a camera is obtained in this paper, the virtual model is rendered into real scenes with OpenGL to realize virtual-real fusion. The experimental results suggest that it costs short time to process complicated natural images with the algorithm proposed in this paper. In case of any illumination change, scale change, rotation in scenes, it is adaptable to complex outdoor environment, showing relatively high timeliness and robustness.