摘要
近年来,随着GPU技术的深入发展和并行算法的日益成熟,使得实时三维重建成为可能。文中实现了一种针对小场景的交互式稠密三维重建系统,此系统借助先进的移动跟踪技术,可以准确地估计相机的即时位置。提出了一种改进的多视深度生成算法,在GPU加速下能够实时计算场景的深度。改进算法中的亚像素级的半全局匹配代价累积提高了多视立体匹配的精度,并结合全局优化的方法计算出了准确的场景深度信息。深度图被转换为距离场,使用全局优化的直方图压缩融合算法和并行的原始对偶算法实现了深度的实时融合。实验结果证明了重建系统的可行性和重建算法的正确性。
In recent years, it is possible to perform real-time 3 D reconstruction with the development of the GPU technology and maturity of parallel algorithms. This paper presents an interactive dense 3 D reconstruction system for small scenes, which can accurately estimate the real-time position of the camera by means of advanced mobile tracking technology. An improved multi-view depth generation algorithm is proposed, which can calculate scene depth in real-time under GPU acceleration. The cumulative cost of sub-pixel semi-global matching in the improved algorithm improves the accuracy of multi-view stereo matching, and combines the global optimization method to calculate the accurate scene depth information. Depth map is converted into distance field, and real-time depth fusion is realized by using globally optimized histogram compression fusion algorithm and parallel primal-dual algorithm. The experimental results prove the feasibility of the reconstruction system and the correctness of the reconstruction algorithm.
引文
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