Automatic Detection and Classi cation of Objects in Point Clouds using multi-stage Semantics

Abstract : Due to the increasing availability of large unstructured point clouds from lasers scanning and photogrammetry, there is a growing demand for automatic evaluation methods. Given the complexity of the underlying problems, several new methods resort to using semantic knowledge in particular for object detection and classification support. In this paper, we present a novel approach, which makes use of advanced algorithms, and benefits from intelligent knowledge management strategies for the processing of 3D point clouds and object classification in a scanned scene. In particular, our method extends the use of semantic knowledge to all stages of the processing, including the guidance of the 3D processing algorithms. The complete solution consists of a multi-stage, iterative, concept based on three factors: the modeled knowledge, the package of algorithms, and the classification engine.
Type de document :
Article dans une revue
Photogrammetrie-Fernerkundung-Geoinformation, 2013, 2013 (3), pp. 221-237(17). <10.1127/1432-8364/2013/0172 1432-8364/13/0172>
Liste complète des métadonnées


https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00875794
Contributeur : Christophe Cruz <>
Soumis le : mercredi 23 octobre 2013 - 14:37:41
Dernière modification le : lundi 13 octobre 2014 - 15:43:25
Document(s) archivé(s) le : vendredi 24 janvier 2014 - 04:24:24

Fichier

PFG_Truong.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Hung Truong, Helmi Ben Hmida, Frank Boochs, Adlane Habed, Christophe Cruz, et al.. Automatic Detection and Classi cation of Objects in Point Clouds using multi-stage Semantics. Photogrammetrie-Fernerkundung-Geoinformation, 2013, 2013 (3), pp. 221-237(17). <10.1127/1432-8364/2013/0172 1432-8364/13/0172>. <hal-00875794>

Partager

Métriques

Consultations de
la notice

521

Téléchargements du document

348