What can projections of flow fields tell us about the visual motion

S. Fejes, L. Davis
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引用次数: 44

Abstract

The dimensionality of visual motion analysis can be reduced by analyzing projections of flow vector fields. In contrast to motion vector fields, these projections exhibit simple geometric properties which are invariant to the scene structure and depend only on the camera motion. Using these properties, structure and motion can be either completely or partially decoupled. We estimate motion parameters from projections of flow fields by using robust techniques, implemented an a reclusive observer model. The model is applicable to general camera motion and to large field of view and requires no point correspondence. We demonstrate our projection method on the problem of detecting independently moving objects from a moving camera. Using the projection approach, the problem can be reduced to a one-dimensional optimization process which involves robust line-fitting and outlier detection. Instantaneous detection measurements are integrated temporally using tracking and spatially applying grouping of coherently moving points.
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关于视觉运动,流场的投影能告诉我们什么
通过分析流矢量场的投影,可以降低视觉运动分析的维数。与运动矢量场相反,这些投影表现出简单的几何属性,这些属性与场景结构无关,仅依赖于摄像机的运动。使用这些属性,结构和运动可以完全或部分解耦。我们使用鲁棒技术从流场的投影中估计运动参数,实现了一个隐式观测器模型。该模型适用于一般摄像机运动和大视场,不需要点对应。我们演示了我们的投影方法在从移动摄像机中检测独立运动物体的问题上。使用投影方法,问题可以简化为一维优化过程,其中包括鲁棒的线拟合和离群值检测。瞬时检测测量在时间上使用跟踪和空间上使用相干移动点分组进行集成。
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