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Vehicle classification using stereo vision

机译:使用立体声视觉的车辆分类

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摘要

A strategy for matching stereo pairs using feature similarity has been developed using the SUSAN corner detector to locate the feature primitives. The use of stereo vision provides information regarding a vehicle's position on the road and allows each object to be clearly distinguished. Using a hypothesis and test strategy, instantiation of models into a scene allows automatic identification of visible and partly visible features. Using a user defined ranking system an image can be tested for distinguishing features. The region of the scene in which to test for the features is defined by the model instantiation. Perspective distortion and camera to viewscreen transformation allows the features to be instantiated in a realistic fashion. The instantiated features can therefore be regarded as templates for matching purposes.
机译:使用苏珊角探测器开发了使用特征相似性匹配立体对的策略来定位特征原语。使用立体声愿景提供有关车辆在道路上的位置的信息,并允许每个对象清楚地区分。使用假设和测试策略,模型将模型的实例化允许自动识别可见和部分可见的功能。使用用户定义的排名系统可以测试图像以进行区分特征。用于测试特征的场景区域由模型实例化定义。透视失真和相机到ViewScreen变换允许以现实的方式实例化的功能。因此,可以将实例化的特征视为用于匹配目的的模板。

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