کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
556091 1451309 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Extracting roads from dense point clouds in large scale urban environment
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
Extracting roads from dense point clouds in large scale urban environment
چکیده انگلیسی

This paper describes a method for extracting roads from a large scale unstructured 3D point cloud of an urban environment consisting of many superimposed scans taken at different times. Given a road map and a point cloud, our system automatically separates road surfaces from the rest of the point cloud. Starting with an approximate map of the road network given in the form of 2D intersection locations connected by polylines, we first produce a 3D representation of the map by optimizing Cardinal splines to minimize the distances to points of the cloud under continuity constraints. We then divide the road network into independent patches, making it feasible to process a large point cloud with a small in-memory working set. For each patch, we fit a 2D active contour to an attractor function with peaks at small vertical discontinuities to predict the locations of curbs. Finally, we output a set of labeled points, where points lying within the active contour are tagged as “road” and the others are not. During experiments with a LIDAR point set containing almost a billion points spread over six square kilometers of a city center, our method provides 86% correctness and 94% completeness.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 66, Issue 6, Supplement, December 2011, Pages S2–S12
نویسندگان
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