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A geometric correspondence feature based-mismatch removal in vision based-mapping and navigation / Zeyu Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 10 (October 2017)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 10 (October 2017) . - pp 693 - 704 Titre : A geometric correspondence feature based-mismatch removal in vision based-mapping and navigation Type de document : Article/Communication Auteurs : Zeyu Li, Auteur ; Jinling Wang, Auteur ; Charles Toth, Auteur Année de publication : 2017 Article en page(s) : pp 693 - 704 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] appariement de données localisées [Termes IGN] attribut géomètrique [Termes IGN] erreur de positionnement [Termes IGN] regroupement de données [Termes IGN] vision par ordinateur Résumé : (auteur) Images with large-area repetitive texture, significant viewpoint, and illumination changes as well as occlusions often induce high-percentage keypoint mismatches, affecting the performance of vision-based mapping and navigation. Traditional methods for mismatch elimination tend to fail when the percentage of mismatches is high. In order to remove mismatches effectively, a new geometry-based approach is proposed in this paper, where Geometric Correspondence Feature (GCF) is used to represent the tentative correspondence. Based on the clustering property of GCFs from correct matches, a new clustering algorithm is developed to identify the cluster formed by the correct matches. With the defined quality factor calculated from the identified cluster, a Progressive Sample Consensus (PROSAC) process integrated with hyperplane-model is employed to further eliminate mismatches. Extensive experiments based on both simulated and real images in indoor and outdoor environments have demonstrated that the proposed approach can significantly improve the performance of mismatch elimination in the presence of high-percentage mismatches. Numéro de notice : A2017-690 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.14358/PERS.83.10.693 En ligne : https://doi.org/10.14358/PERS.83.10.693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87856 [article]