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Novel method for vehicle and pedestrian detection based on information fusion

机译:基于信息融合的车辆和行人检测的一种新方法

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摘要

A novel approach for vehicle and pedestrian detection based on data fusion techniques is presented. The work fuses information from a 2D laser scanner and a computer camera, to provide detection and classification of vehicles and pedestrians in road environments. Thanks to the data fusion approach, the limitations of each sensor are overcome. Thus reliable system is provided, fulfilling the demands of road safety applications. Classification is performed using each sensor independently. Laser scanner approach is based in pattern matching and vision approach is based in the classical Histogram of Oriented Gradients features approach. A higher stage performs data fusion using Kalman Filter and Global Nearest Neighbors.
机译:提出了一种基于数据融合技术的车辆和行人检测新方法。这项工作融合了来自2D激光扫描仪和计算机摄像机的信息,以提供道路环境中车辆和行人的检测和分类。由于采用了数据融合方法,因此克服了每个传感器的局限性。因此提供了可靠的系统,满足了道路安全应用的需求。使用每个传感器独立进行分类。激光扫描仪方法基于模式匹配,视觉方法基于经典的“梯度直方图”特征方法。较高的阶段使用卡尔曼滤波器和全局最近邻居执行数据融合。

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