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Grand Challenge: 3-D Urban Objects Detection and Classification From Point Clouds

Alkhalili, Yassin ; Luthra, Manisha ; Rizk, Amr ; Koldehofe, Boris (2019)
Grand Challenge: 3-D Urban Objects Detection and Classification From Point Clouds.
DEBS'19 - 13th ACM International Conference on Distributed and Event-based Systems. Darmstadt, Germany (24.-28. June)
Conference or Workshop Item, Bibliographie

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

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Alkhalili, Yassin ; Luthra, Manisha ; Rizk, Amr ; Koldehofe, Boris
Type of entry: Bibliographie
Title: Grand Challenge: 3-D Urban Objects Detection and Classification From Point Clouds
Language: English
Date: June 2019
Event Title: DEBS'19 - 13th ACM International Conference on Distributed and Event-based Systems
Event Location: Darmstadt, Germany
Event Dates: 24.-28. June
URL / URN: https://doi.org/10.1145/3328905.3330298
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

Uncontrolled Keywords: Object Recognition, Point Cloud, Ensemble of Shape Functions, ESF, PCL
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Multimedia Communications
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms > Subproject B4: Planning
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms > Subproject C2: Information-centred perspective
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms > Subproject C3: Content-centred perspective
Date Deposited: 17 Jun 2019 08:22
Last Modified: 14 Apr 2020 10:05
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