کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6949674 | 1451281 | 2014 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning](/preview/png/6949674.png)
چکیده انگلیسی
We propose an automatic and robust approach to detect, segment and classify urban objects from 3D point clouds. Processing is carried out using elevation images and the result is reprojected onto the 3D point cloud. First, the ground is segmented and objects are detected as discontinuities on the ground. Then, connected objects are segmented using a watershed approach. Finally, objects are classified using SVM with geometrical and contextual features. Our methodology is evaluated on databases from Ohio (USA) and Paris (France). In the former, our method detects 98% of the objects, 78% of them are correctly segmented and 82% of the well-segmented objects are correctly classified. In the latter, our method leads to an improvement of about 15% on the classification step with respect to previous works. Quantitative results prove that our method not only provides a good performance but is also faster than other works reported in the literature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 93, July 2014, Pages 243-255
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 93, July 2014, Pages 243-255
نویسندگان
Andrés Serna, Beatriz Marcotegui,