单目图像序列中目标的深度检测

Hong Guo, Yi Lu, S. Sarka
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引用次数: 9

摘要

本文描述了一种从单目图像序列中恢复运动目标结构的方法。在本文中,我们假设相机是静止的。我们首先使用一种运动检测算法来检测运动目标,该算法基于四种启发式算法,这些启发式算法来源于运动车辆的特性,即最大速度、小速度变化、相干和连续运动。第二种算法使用一种过度约束的方法来估计运动目标的距离。我们将展示一个来自合成数据的概念验证示例。我们已经将该方法应用于移动摄像机捕获的单眼图像序列,以恢复静止目标(如树木,电线杆等)的三维结构。本文还介绍了在室外环境下捕获的单眼图像序列的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Depth detection of targets in a monocular image sequence
This paper describes an approach for recovering structure of a moving target from a monocular image sequence. Within this paper, we assume the camera is stationary. We first use a motion detection algorithm to detect moving targets based on four heuristics derived from the properties of moving vehicles, maximum velocity, small velocity changes, coherent, and continuous motion. The second algorithm then estimates the distance of the moving targets using an over-constrained approach. We will show a proof-of-concept example from synthetic data. We have applied the approach to monocular image sequences captured by a moving camera to recover the 3D structure of stationary targets such as trees, telephone pole, etc. The experimental results on a monocular image sequence captured in an outdoor environment are also presented.
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