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In this letter, we present a new approach for object classification in continuously streamed Lidar point clouds collected from urban areas. The input of our framework is raw 3-D point cloud sequences captured by a Velodyne HDL-64 Lidar, and we aim to extract all vehicles and pedestrians in the neighborhood of the moving sensor. We propose a complete pipeline developed especially for distinguishing...
In urban environments, object recognition and road monitoring are key issues for driving assistance systems or autonomous vehicles. This paper presents a LIDAR-based perception system which provides reliable detection of 3D urban objects from point cloud sequences of a Velodyne HDL-64E terrestrial LIDAR scanner installed on a moving platform. As for the output of the system, we perform real-time localization...
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