Segmentation of Vehicles and Roads by a Low-Channel Lidar
An effective method to segment vehicles and roads is proposed for autonomous vehicles using low-channel 3D lidar. The distance-view transformation is newly proposed to overcome the low density of top-view data of lidar. In addition, a dilated convolution structure is proposed to expand the receptive...
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Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2019-11, Vol.20 (11), p.4251-4256 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | An effective method to segment vehicles and roads is proposed for autonomous vehicles using low-channel 3D lidar. The distance-view transformation is newly proposed to overcome the low density of top-view data of lidar. In addition, a dilated convolution structure is proposed to expand the receptive field of a convolutional neural network. The proposed network improves the accuracy of segmentation. The experimental results are presented to verify the usefulness of the proposed method. |
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ISSN: | 1524-9050 1558-0016 |
DOI: | 10.1109/TITS.2019.2903529 |