Active shape model precision analysis of vehicle detection in 3D lidar point clouds

Originalpublikation

Busch, S.: Active shape model precision analysis of vehicle detection in 3D lidar point clouds. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 42 (2019), Nr. 2/W13, S. 21-26. DOI: https://doi.org/10.5194/isprs-archives-XLII-2-W13-21-2019

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Zum Zitieren der Version im Repositorium verwenden Sie bitte diesen DOI: https://doi.org/10.15488/10154

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Zusammenfassung:
LiDAR systems are frequently used for driver assistance systems. The minimal distance to other objects and the exact pose of a vehicle is important for ego movement prediction. Therefore, in this work, we extract the poses of vehicles from LiDAR point clouds. To this end, we measure them with LiDAR, segment the vehicle points and extract the pose. Further, we analyze the influence of LiDAR resolutions on the pose extraction by active shape models (ASM) and by the center of bounding boxes combined with the principal component analysis (BC-PCA). © Authors 2019.
Lizenzbestimmungen: CC BY 4.0 Unported - https://creativecommons.org/licenses/by/4.0/
Publikationstyp: Article
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2019
Schlagwörter (englisch): Active Shape Model, LiDAR, Point Cloud, Pose Estimation, Segmentation, Vehicle Detection, Automobile drivers, Image segmentation, Motion estimation, Optical radar, Vehicles, Active shape model, Active Shape Models, Driver assistance system, Lidar point clouds, Movement prediction, Point cloud, Pose estimation, Vehicle detection, Principal component analysis
Fachliche Zuordnung (DDC): 550 | Geowissenschaften
Kontrollierte Schlagwörter: Konferenzschrift

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