Grand Challenge: 3-D Urban Objects Detection and Classification From Point Clouds
Key: ALRK19-1
Author: Yassin Alkhalili, Manisha Luthra, Amr Rizk, Boris Koldehofe
Date: June 2019
Kind: In proceedings
Publisher: ACM
Book title: Proceedings of The 13th ACM International Conference on Distributed and Event-based Systems (DEBS ’19)
Keywords: Object Recognition, Point Cloud, Ensemble of Shape Functions, ESF, PCL
Abstract: In this paper, we present our approach to solve the DEBS Grand challenge 2019 which consists of classifying urban objects in different scenes that originate from a LiDAR sensor. In general, at any point in time, LiDAR data can be considered as a point cloud where a reliable feature extractor and a classification model are required to be able to recognize 3-D objects in such scenes. Herein, we propose and describe an implementation of a 3-D point cloud object detection and classification system based on a 3-D global feature called Ensemble of Shape Functions (ESF) and a random forest object classifier
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