Scipediacontent: Scipediacontent moved page Draft Content 339686958 to Guo et al 2020a

2021-02-12T15:17:07Z

Scipediacontent moved page Draft Content 339686958 to Guo et al 2020a

Scipediacontent: Created page with " == Abstract == Moving object classification is essential for autonomous vehicle to complete high-level tasks like scene understanding and motion planning. In this paper, we..."

2021-02-12T15:17:04Z

Created page with " == Abstract == Moving object classification is essential for autonomous vehicle to complete high-level tasks like scene understanding and motion planning. In this paper, we..."

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== Abstract ==

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.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_339686958-beopen556-5130-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1155/2020/1583129 http://dx.doi.org/10.1155/2020/1583129] under the license http://creativecommons.org/licenses/by/4.0/

* [https://doi.org/10.1155/2020/1583129 https://doi.org/10.1155/2020/1583129]

* [http://downloads.hindawi.com/journals/jat/2020/1583129.pdf http://downloads.hindawi.com/journals/jat/2020/1583129.pdf],
: [http://downloads.hindawi.com/journals/jat/2020/1583129.xml http://downloads.hindawi.com/journals/jat/2020/1583129.xml],
: [http://dx.doi.org/10.1155/2020/1583129 http://dx.doi.org/10.1155/2020/1583129] under the license cc-by

* [http://dx.doi.org/10.1155/2020/1583129 http://dx.doi.org/10.1155/2020/1583129],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2020/1583129 https://www.hindawi.com/journals/jat/2020/1583129],
: [http://downloads.hindawi.com/journals/jat/2020/1583129.pdf http://downloads.hindawi.com/journals/jat/2020/1583129.pdf],
: [https://academic.microsoft.com/#/detail/3011866578 https://academic.microsoft.com/#/detail/3011866578]

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Scipediacontent: Scipediacontent moved page Draft Content 339686958 to Guo et al 2020a

Scipediacontent: Created page with " == Abstract == Moving object classification is essential for autonomous vehicle to complete high-level tasks like scene understanding and motion planning. In this paper, we..."