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Shadow detection for vehicles by locating the object-shadow boundary

机译:通过定位物体阴影边界来检测车辆的阴影

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摘要

We introduce in this paper a shadow detection method for vehicles in traffic video sequences. Our method approximates the boundary between vehicles and their associated shadows by one or more straight lines. These lines are located in the image by exploiting both local information (e.g. statistics in intensity differences) and global information (e.g. principal edge directions). The proposed method does not assume a particular lighting condition, and requires no human interaction nor parameter training. Experiments on practical real-world traffic video sequences demonstrate that our method is simple, robust and efficient under traffic scenes with different lighting conditions. Accurate positioning of target vehicles is thus achieved even in the presence of cast shadows.
机译:我们在本文中介绍了一种在交通视频序列中对车辆进行阴影检测的方法。我们的方法通过一条或多条直线近似车辆及其相关阴影之间的边界。通过利用局部信息(例如强度差异的统计数据)和全局信息(例如主要边缘方向)两者来将这些线定位在图像中。所提出的方法不假定特定的照明条件,并且不需要人工干预也不需要参数训练。在实际的现实交通视频序列上进行的实验表明,在不同光照条件下的交通场景下,我们的方法简单,可靠且有效。因此即使在存在投射阴影的情况下也可以实现目标车辆的准确定位。

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