Solid or not solid: vision for radar target validation

A. Solé, O. Mano, G. Stein, H. Kumon, Y. Tamatsu, A. Shashua
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引用次数: 55

Abstract

In the context of combining radar and vision sensors for a fusion application in dense city traffic situations, one of the major challenges is to be able to validate radar targets. We take a high-level fusion approach assuming that both sensor modalities have the capacity to independently locate and identify targets of interest. In this context, radar targets can either correspond to a vision target- in which case the target is validated without further processing- or not. It is the latter case that drives the focus of this paper. A non-matched radar target can correspond to some solid object which is not part of the objects of interest of the vision sensor (such as a guard-rail) or can be caused by reflections in which case it is a ghost target which does not match any physical object in the real world. We describe a number of computational steps for the decision making of non-matched radar targets. The computations combine both direct motion parallax measurements and indirect motion analysis- which are not sufficient for computing parallax but are nevertheless quite effective- and pattern classification steps for covering situations which motion analysis are weak or ineffective. One of the major advantages of our high-level fusion approach is that it allows the use of simpler (low cost) radar technology to create a combined high performance system.
固体或不固体:雷达目标验证的视觉
在将雷达和视觉传感器相结合以实现密集城市交通场景融合应用的背景下,能够验证雷达目标是主要挑战之一。我们采用高水平的融合方法,假设两种传感器模式都有能力独立定位和识别感兴趣的目标。在这种情况下,雷达目标可以对应于视觉目标——在这种情况下,目标不需要进一步处理就可以被验证——或者不对应。后一种情况才是本文的重点。一个不匹配的雷达目标可以对应于一些固体物体,这些物体不是视觉传感器感兴趣的物体的一部分(例如护栏),或者可以由反射引起,在这种情况下,它是一个幽灵目标,与现实世界中的任何物理物体都不匹配。描述了非匹配雷达目标决策的计算步骤。计算结合了直接运动视差测量和间接运动分析-这不足以计算视差,但仍然相当有效-以及覆盖运动分析薄弱或无效的情况的模式分类步骤。我们的高水平融合方法的主要优点之一是,它允许使用更简单(低成本)的雷达技术来创建一个综合的高性能系统。
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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