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Three-dimensional reconstruction of binocular stereo vision based on improved SURF algorithm and KD-Tree matching algorithm

机译:基于改进的SURF算法和KD-Tree匹配算法的双目立体视觉三维重建

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摘要

With the constant development of computer science and technology, binocular stereo vision as a special form of computer vision plays a vital role in implementing computer change detection, image correction, three-dimensional reconstruction, and is widely applied in computer vision fields such as aerial mapping, visual navigation, motion analysis and industrial inspection. However, as it is difficult to perform binocular stereo vision, and precise parallax principle and mathematical method are required. Thus this study rapidly and effectively realizes three-dimensional reconstruction of binocular stereo vision by feature description vector generated by improved surface (SURF) algorithm combined with K-dimension tree (KD-Tree) searching. Effective combination of improved SURF algorithm and KD-Tree significantly enhances sense of reality of three-dimensional scene.
机译:随着计算机科学技术的不断发展,双目立体视觉作为计算机视觉的一种特殊形式,在实现计算机变化检测,图像校正,三维重构中起着至关重要的作用,并广泛应用于航空测绘等计算机视觉领域。 ,视觉导航,运动分析和工业检查。然而,由于难以执行双目立体视觉,因此需要精确的视差原理和数学方法。因此,本研究通过改进曲面(SURF)算法生成的特征描述向量与K维树(KD-Tree)搜索相结合,快速有效地实现了双目立体视觉的三维重建。改进的SURF算法与KD-Tree的有效结合可显着增强三维场景的真实感。

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