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Building Pedestrian Contour Hierarchies for Improving Detection in Traffic Scenes

机译:建立行人轮廓层次结构以改善交通场景中的检测

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This paper presents a new method for extracting pedestrian contours from images using 2D and 3D information obtained from a stereo-vision acquisition system. Two pedestrian contour types are extracted. First is obtained from static pedestrian confidence images using fixed background scenes and second from general traffic scenes having variable background. A robust approach for building contour hierarchies of these contours is then presented. First hierarchy is built of "perfect" contours extracted from fixed background scenes and the second one is built of "imperfect" contours extracted from images with variable background. The objective is to evaluate the two hierarchies in order to identify the best one for real time pedestrian detection.
机译:本文提出了一种使用从立体视觉采集系统获得的2D和3D信息从图像中提取行人轮廓的新方法。提取两种行人轮廓类型。首先从使用固定背景场景的静态行人信心图像获得,其次从具有可变背景的一般交通场景获得。然后介绍了一种构建这些轮廓的轮廓层次结构的可靠方法。第一个层次结构是从固定背景场景中提取的“完美”轮廓,第二个层次结构是从背景可变的图像中提取的“不完美”轮廓。目的是评估两个层次结构,以便为实时行人检测确定最佳层次结构。

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