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

Xiangjie Li, Xuzhi Wang, Cheng Cheng
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引用次数: 2

Abstract

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.
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基于快速ER和surf算法的场景识别技术在增强现实中的应用
针对增强现实中空间配准结果的不及时性、不准确性和不稳定性等问题,本文提出了一种基于FAST-ER (Features from Accelerated Segment Test)和SURF (Accelerated Robust Features)的改进算法,不仅改进了特征点提取过程中决策树的递归调整方法,同时也克服了传统FAST-ER算法计算量大、特征点提取效率低等问题。本文在获取摄像机的位置参数信息后,利用OpenGL将虚拟模型渲染到真实场景中,实现虚实融合。实验结果表明,本文提出的算法处理复杂的自然图像所需的时间短。在场景中发生光照变化、尺度变化、旋转等情况时,能适应复杂的室外环境,表现出较高的时效性和鲁棒性。
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