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Understanding of wheelchair ramp scenes for disabled people with visual impairments

机译:了解视力障碍者的轮椅坡道场景

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Helping disabled people with visual impairments understand wheelchair ramp scenes has considerable value in computer vision. However, due to the diversity of wheelchair ramp scenes, understanding them remains a big challenge. Wheelchair ramp planes can be considered as a composition of rectangles that do not satisfy manhattan assumption. These non-manhattan rectangles are projected into two dimensional projections, shaping into special geometric configurations, which may enable us to estimate their original orientation and position in 3D scenes. In this paper, we presented a method for disabled people with visual impairments to understand wheelchair ramp scenes from a single image without any prior training. Firstly angle projections can be assigned to different clusters. Secondly ramp vanishing points (RVPs) can be estimated. Then it is possible to determine ramp planes consisting of angle projections that belong to the estimated RVPs. Finally, the algorithm can understand wheelchair ramp scenes including not only manhattan structures but also ramp planes belonging to non-manhattan structures. The proposed approach requires no prior training or any knowledge of the camera's internal parameters. Besides, it is robust to the errors in calibration and image noise. We compared the estimated wheelchair ramp scene layout against the ground truth, measuring the percentage of pixels that were incorrectly classified. The experimental results showed that the method can understand wheelchair ramp scenes including not only manhattan structures but also non-manhattan structures of ramp planes, making it practical and efficient for disabled people with visual impairments.
机译:帮助视力障碍的残疾人了解轮椅坡道场景在计算机视觉方面具有相当大的价值。然而,由于轮椅坡道场景的多样性,对它们的了解仍然是一个巨大的挑战。轮椅坡道平面可以看作是不满足曼哈顿假设的矩形组成。这些非曼哈顿矩形被投影为二维投影,并成形为特殊的几何配置,这使我们能够估计其在3D场景中的原始方向和位置。在本文中,我们提出了一种用于视力障碍残疾人无需事先培训即可从单个图像了解轮椅坡道场景的方法。首先,可以将角度投影分配给不同的群集。其次,可以估计坡道消失点(RVP)。然后可以确定由属于估计的RVP的角度投影组成的斜坡平面。最后,该算法可以理解轮椅坡道场景,不仅包括曼哈顿结构,还包括非曼哈顿结构的坡道平面。所提出的方法不需要事先培训或对相机内部参数的任何了解。此外,它对于校准和图像噪声中的误差也很鲁棒。我们将估计的轮椅坡道场景布局与地面真实情况进行了比较,测量了错误分类的像素百分比。实验结果表明,该方法不仅可以理解轮椅坡道场景,不仅可以了解曼哈顿斜面的结构,还可以了解非曼哈顿结构的斜面场景,对视力障碍者具有实用性和有效性。

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