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Moving Object Classification Using 3D Point Cloud in Urban Traffic Environment
Joint Authors
Fu, Rui
Zhang, MingFang
Guo, YingShi
Wang, Li
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-17
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Moving object classification is essential for autonomous vehicle to complete high-level tasks like scene understanding and motion planning.
In this paper, we propose a novel approach for classifying moving objects into four classes of interest using 3D point cloud in urban traffic environment.
Unlike most existing work on object recognition which involves dense point cloud, our approach combines extensive feature extraction with the multiframe classification optimization to solve the classification task when partial occlusion occurs.
First, the point cloud of moving object is segmented by a data preprocessing procedure.
Then, the efficient features are selected via Gini index criterion applied to the extended feature set.
Next, Bayes Decision Theory (BDT) is employed to incorporate the preliminary results from posterior probability Support Vector Machine (SVM) classifier at consecutive frames.
The point cloud data acquired from our own LIDAR as well as public KITTI dataset is used to validate the proposed moving object classification method in the experiments.
The results show that the proposed SVM-BDT classifier based on 18 selected features can effectively recognize the moving objects.
American Psychological Association (APA)
Zhang, MingFang& Fu, Rui& Guo, YingShi& Wang, Li. 2020. Moving Object Classification Using 3D Point Cloud in Urban Traffic Environment. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1175353
Modern Language Association (MLA)
Zhang, MingFang…[et al.]. Moving Object Classification Using 3D Point Cloud in Urban Traffic Environment. Journal of Advanced Transportation No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1175353
American Medical Association (AMA)
Zhang, MingFang& Fu, Rui& Guo, YingShi& Wang, Li. Moving Object Classification Using 3D Point Cloud in Urban Traffic Environment. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1175353
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175353