A fast dense stereo matching algorithm with an application to 3D occupancy mapping using quadrocopters

Radouane Ait Jellal, A. Zell
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引用次数: 4

Abstract

We propose a fast algorithm for computing stereo correspondences and correcting the mismatches. The correspondences are computed using stereo block matching and refined with a depth-aware method. We compute 16 disparities at the same time using SSE instructions. We evaluated our method on the Middlebury benchmark and obtained promosing results for practical realtime applications. The use of SSE instructions allows us to reduce the time needed to process the Tsukuba stereo pair to 8 milliseconds (125 fps) on a Core i5 CPU with 2×3.3 GHz. Our disparity refinement method has corrected 40% of the wrong matches with an additional computational time of 5.2% (0.41ms). The algorithm has been used to build 3D occupancy grid maps from stereo images. We used the datasets provided by the EuRoC Robotic Challenge. The reconstruction was accurate enough to perform realtime safe navigation.
一种快速密集立体匹配算法,应用于使用四旋翼飞行器的三维占用映射
我们提出了一种快速计算立体对应并校正不匹配的算法。使用立体块匹配计算对应关系,并使用深度感知方法进行细化。我们使用SSE指令同时计算16个差异。我们在Middlebury基准上对我们的方法进行了评估,并获得了实际实时应用的推广结果。SSE指令的使用使我们能够将处理筑波立体声对所需的时间减少到8毫秒(125 fps),在酷睿i5 CPU上使用2×3.3 GHz。我们的视差细化方法校正了40%的错误匹配,增加了5.2% (0.41ms)的计算时间。该算法已被用于从立体图像构建三维占用网格地图。我们使用了欧洲机器人挑战赛提供的数据集。重建足够精确,可以进行实时安全导航。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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