To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

中文翻译：

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双目立体视觉在室内环境中对运动目标的高精度识别和定位

为了获得有效的室内运动目标定位，提出了一种基于双目立体视觉的可靠稳定的运动目标定位方法。提出了一种移动目标识别提取算法，该算法集成了位移金字塔Horn-Schunck（HS）光流，Delaunay三角剖分和Otsu阈值分割，可将移动目标与复杂背景分开，称为Otsu Delaunay HS（O-DHS）方法。此外，提出了一种基于深度匹配和立体视觉的立体声匹配算法，以获得密集的立体声匹配点对，称为立体声深度匹配（S-DM）。提取移动目标的立体匹配点对以及移动目标区域和立体深度匹配点对，然后根据双目视觉的平行结构原理，重建了运动目标区域中各点的三维坐标。最后，通过质心法确定了移动目标。实验结果表明，该方法能够较好地抵抗图像噪声和重复纹理，可以有效地检测和分离运动目标，并且可以更加准确，稳定地匹配重复纹理区域中的立体图像点。该方法可以有效地提高三维运动目标坐标的有效性，准确性和鲁棒性。可以有效地检测和分离运动目标，并且可以在重复的纹理区域中更准确地匹配立体图像点并保持稳定性。该方法可以有效地提高三维运动目标坐标的有效性，准确性和鲁棒性。可以有效地检测和分离运动目标，并且可以在重复的纹理区域中更准确地匹配立体图像点并保持稳定性。该方法可以有效地提高三维运动目标坐标的有效性，准确性和鲁棒性。