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Automatic registration of mobile mapping system Lidar points and panoramic-image sequences by relative orientation model / Ningning Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 12 (December 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 12 (December 2021) . - pp 913 - 922 Titre : Automatic registration of mobile mapping system Lidar points and panoramic-image sequences by relative orientation model Type de document : Article/Communication Auteurs : Ningning Zhu, Auteur ; Bisheng Yang, Auteur ; Zhen Dong, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 913 - 922 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] appariement de points [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction de traits caractéristiques [Termes IGN] image panoramique [Termes IGN] modèle géométrique de prise de vue [Termes IGN] orientation relative [Termes IGN] scène urbaine [Termes IGN] semis de points [Termes IGN] séquence d'images [Termes IGN] superposition de données [Termes IGN] SURF (algorithme) Résumé : (Auteur) To register mobile mapping system (MMS) lidar points and panoramic-image sequences, a relative orientation model of panoramic images (PROM) is proposed. The PROM is suitable for cases in which attitude or orientation parameters are unknown in the panoramic-image sequence. First, feature points are extracted and matched from panoramic-image pairs using the SURF algorithm. Second, these matched feature points are used to solve the relative attitude parameters in the PROM. Then, combining the PROM with the absolute position and attitude parameters of the initial panoramic image, the MMS lidar points and panoramic-image sequence are registered. Finally, the registration accuracy of the PROM method is assessed using corresponding points manually selected from the MMS lidar points and panoramic-image sequence. The results show that three types of MMS data sources are registered accurately based on the proposed registration method. Our method transforms the registration of panoramic images and lidar points into image feature-point matching, which is suitable for diverse road scenes compared with existing methods. Numéro de notice : A2021-899 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00006R2 Date de publication en ligne : 01/12/2021 En ligne : https://doi.org/10.14358/PERS.21-00006R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99298 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021121	SL	Revue	Centre de documentation	Revues en salle	Disponible

Semiautomatically register MMS LiDAR points and panoramic image sequence using road lamp and lane / Ningning Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 11 (November 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 11 (November 2019) . - pp 829 - 840 Titre : Semiautomatically register MMS LiDAR points and panoramic image sequence using road lamp and lane Type de document : Article/Communication Auteurs : Ningning Zhu, Auteur ; Yonghong Jia, Auteur ; Xia Huang, Auteur Année de publication : 2019 Article en page(s) : pp 829 - 840 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] appariement de points [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] éclairage public [Termes IGN] extraction de points [Termes IGN] image panoramique [Termes IGN] mobilier urbain [Termes IGN] semis de points [Termes IGN] séquence d'images [Termes IGN] transformation linéaire directe Résumé : (Auteur) We propose using the feature points of road lamp and lane to register mobile mapping system (MMS) LiDAR points and panoramic image sequence. Road lamp and lane are the common objects on roads; the spatial distributions are regular, and thus our registration method has wide applicability and high precision. First, the road lamp and lane were extracted from the LiDAR points by horizontal grid and reflectance intensity and then by optimizing the endpoints as the feature points of road lamp and lane. Second, the feature points were projected onto the panoramic image by initial parameters and then by extracting corresponding feature points near the projection location. Third, the direct linear transformation method was used to solve the registration model and eliminate mismatching feature points. In the experiments, we compare the accuracy of our registration method with other registration methods by a sequence of panoramic images. The results show that our registration method is effective; the registration accuracy of our method is less than 10 pixels and averaged 5.84 pixels in all 31 panoramic images (4000 × 8000 pixels), which is much less than that of the 56.24 pixels obtained by the original registration method. Numéro de notice : A2019-525 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.14358/PERS.85.11.829 Date de publication en ligne : 01/11/2019 En ligne : https://doi.org/10.14358/PERS.85.11.829 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94062 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019111	RAB	Revue	Centre de documentation	En réserve L003	Disponible