Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이민수 | * |
dc.date.accessioned | 2017-03-01T01:03:01Z | - |
dc.date.available | 2017-03-01T01:03:01Z | - |
dc.date.issued | 2017 | * |
dc.identifier.issn | 2150-704X | * |
dc.identifier.other | OAK-20196 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/234650 | - |
dc.description.abstract | The object-based point cloud analysis (OBPCA) method has been used for vehicle detection from airborne light detection and ranging (LiDAR) point clouds with a relatively simple process and exhibits a degree of accuracy as high as that of a three-dimensional point cloud-based detection scheme. However, it only utilizes horizontal features of the segmented point clouds, and it uses thresholds established by heuristic observation and experience. In this article, we present a novel method for vehicle detection from airborne LiDAR point clouds based on a decision tree algorithm with horizontal and vertical features. It calculates the horizontal and vertical features for segments created by the filtering and segmentation processes, and it establishes a vehicle detection model by training a decision tree classifier with horizontal and vertical features of the segments. Our experiment shows that our proposed method outperforms the previous method in terms of recall and precision by 13.14% and 30.02%, respectively. © 2017 Informa UK Limited, trading as Taylor & Francis Group. | * |
dc.language | English | * |
dc.publisher | Taylor and Francis Ltd. | * |
dc.subject | decision tree | * |
dc.subject | LiDAR point clouds | * |
dc.subject | OBPCA | * |
dc.subject | vehicle detection | * |
dc.title | Vehicle detection from airborne LiDAR point clouds based on a decision tree algorithm with horizontal and vertical features | * |
dc.type | Article | * |
dc.relation.issue | 5 | * |
dc.relation.volume | 8 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 409 | * |
dc.relation.lastpage | 418 | * |
dc.relation.journaltitle | Remote Sensing Letters | * |
dc.identifier.doi | 10.1080/2150704X.2016.1278310 | * |
dc.identifier.wosid | WOS:000394460300002 | * |
dc.identifier.scopusid | 2-s2.0-85011982889 | * |
dc.author.google | Eum J. | * |
dc.author.google | Bae M. | * |
dc.author.google | Jeon J. | * |
dc.author.google | Lee H. | * |
dc.author.google | Oh S. | * |
dc.author.google | Lee M. | * |
dc.contributor.scopusid | 이민수(56142596700) | * |
dc.date.modifydate | 20240322133738 | * |