Affine trackability aids obstacle detection

H. Sawhney, A. Hanson
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引用次数: 4

Abstract

Potential obstacles in the path of a mobile robot that can often be characterized as shallow (i.e., their extent in depth is small compared to their distance from the camera) are considered. The constraint of affine trackability is applied to automatic identification and 3-D reconstruction of shallow structures in realistic scenes. It is shown how this approach can handle independent object motion, occlusion, and motion discontinuity. Although the reconstructed structure is only a frontal plane approximation to the corresponding real structure, the robustness of depth of the approximation might be useful for obstacle avoidance, where the exact shape of an object may not be of consequence so long as collisions with it can be avoided.<>
仿射跟踪性有助于障碍物检测
考虑移动机器人路径上的潜在障碍物,这些障碍物通常可以被描述为浅(即,与它们与相机的距离相比,它们的深度范围很小)。将仿射可跟踪性约束应用于现实场景中浅层结构的自动识别和三维重建。它显示了这种方法如何处理独立的对象运动,遮挡和运动不连续。虽然重建的结构只是对应真实结构的正面平面近似,但近似深度的鲁棒性可能对避障有用,在避障中,只要可以避免与物体碰撞,物体的确切形状可能并不重要。
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