Détail de l'auteur
Auteur A. Stefanidis |
Documents disponibles écrits par cet auteur (6)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Orientation of ground-level motion imagery using building facades / A. Stefanidis in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 9 (September 2006)
[article]
Titre : Orientation of ground-level motion imagery using building facades Type de document : Article/Communication Auteurs : A. Stefanidis, Auteur ; C. Georgidis, Auteur ; Peggy Agouris, Auteur Année de publication : 2006 Article en page(s) : pp 1061 - 1072 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes IGN] acquisition d'images
[Termes IGN] angle de visée
[Termes IGN] bati
[Termes IGN] correction d'image
[Termes IGN] milieu urbain
[Termes IGN] orientation du capteur
[Termes IGN] orientation externe
[Termes IGN] prise de vue terrestreRésumé : (Auteur) In this paper, we address the orientation of ground-level motion imagery captured by sensors roaming in an urban area. We investigate the use of building façades (instead of traditional points), as matching features for ground-level motion imagery orientation. We assume a situation where few images in our sequence are already absolutely oriented, and present a novel approach to orient all remaining in between image sequences relative to them. This innovative version of dependent orientation allows us to propagate orientation information within sequences of ground level imagery, establishing a novel orientation scheme. Experimental results show accuracies on the order of 0.18 to 0.29 degrees in rotation estimation, and 0.17 to 0.29 meters in camera position determination. Copyright ASPRS Numéro de notice : A2006-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.9.1061 En ligne : https://doi.org/10.14358/PERS.72.9.1061 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28107
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 9 (September 2006) . - pp 1061 - 1072[article]Reconstructing spatiotemporal trajectories from sparse data / P. Partsinevelos in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 1 (December 2005 - March 2006)
[article]
Titre : Reconstructing spatiotemporal trajectories from sparse data Type de document : Article/Communication Auteurs : P. Partsinevelos, Auteur ; Peggy Agouris, Auteur ; A. Stefanidis, Auteur Année de publication : 2005 Article en page(s) : pp 3 - 16 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de groupement
[Termes IGN] carte de Kohonen
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données spatiotemporelles
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] segmentation
[Termes IGN] seuillageRésumé : (Auteur) In motion imagery-based tracking applications, it is common to extract locations of moving objects without any knowledge about the identity of the objects they correspond to. The identification of individual spatiotemporal trajectories from such data sets is far from trivial when these trajectories intersect in space, time, or attributes. In this paper, we present a novel approach for the reconstruction of entangled spatiotemporal trajectories of moving objects captured in motion imagery data sets. We have developed AGENT (Attribute-aided Classification of Entangled Trajectories), a novel framework that comprises classification, clustering, and neural net processes to progressively reconstruct elongated trajectories using as input spatiotemporal coordinates of image patches and corresponding attribute values. AGENT proceeds by first forming brief fragments and then linking them and adding points to them. An initial classification allows us to form brief segments corresponding to distinct objects. These segments are then linked together through clustering to form longer trajectories. Back-propagation neural network classification and geometric/self-organizing map (SOM) analysis refine these trajectories by removing misclassified and redistributing unassigned points. Thus, AGENT integrates some established classification and clustering tools to devise a novel approach that can address the tracking challenges of busy environments. Furthermore, AGENT allows us use spatiotemporal (ST) thresholds to cluster trajectories according to their spatial and temporal extent. In the paper, we present in detail our framework and experimental results that support the application potential of our approach. Numéro de notice : A2006-218 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.10.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27945
in ISPRS Journal of photogrammetry and remote sensing > vol 60 n° 1 (December 2005 - March 2006) . - pp 3 - 16[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 081-06011 SL Revue Centre de documentation Revues en salle Disponible Automated road extraction from high resolution multispectral imagery / P. Doucette in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 12 (December 2004)
[article]
Titre : Automated road extraction from high resolution multispectral imagery Type de document : Article/Communication Auteurs : P. Doucette, Auteur ; Peggy Agouris, Auteur ; A. Stefanidis, Auteur Année de publication : 2004 Article en page(s) : pp 1405 - 1416 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] axe médian
[Termes IGN] bande infrarouge
[Termes IGN] banlieue
[Termes IGN] classification dirigée
[Termes IGN] extraction automatique
[Termes IGN] extraction du réseau routier
[Termes IGN] image à haute résolution
[Termes IGN] image en couleur
[Termes IGN] image multibande
[Termes IGN] logique floue
[Termes IGN] milieu urbain
[Termes IGN] parallélisme
[Termes IGN] topologieRésumé : (Auteur) This work presents a novel methodology for fully automated road centerline extraction that exploits spectral content from high resolution multispectral images. Preliminary detection of candidate road centerline components is performed with Anti-parallel-edge Centerline Extraction (ACE). This is followed by constructing a road vector topology with a fuzzy grouping model that links nodes from a self-organized mapping of the ACE components. Following topology construction, a Self-Supervised Road Classification (SSRC) feedback loop is implemented to automate the process of training sample selection and refinement for a road class, as well as deriving practical spectral definitions for non-road classes. SSRC demonstrates a potential to provide dramatic improvement in road extraction results by exploiting spectral content. Road centerline extraction results are presented for three 1 m color infrared suburban scenes which show significant improvement following SSRC. Numéro de notice : A2004-502 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.70.12.1405 En ligne : https://doi.org/10.14358/PERS.70.12.1405 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27019
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 12 (December 2004) . - pp 1405 - 1416[article]Supporting quality-based image retrieval through user preference learning / Giorgos Mountrakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 8 (August 2004)
[article]
Titre : Supporting quality-based image retrieval through user preference learning Type de document : Article/Communication Auteurs : Giorgos Mountrakis, Auteur ; A. Stefanidis, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 973 - 981 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] apprentissage automatique
[Termes IGN] indicateur de qualité
[Termes IGN] intelligence artificielle
[Termes IGN] qualité d'image
[Termes IGN] requête spatiale
[Termes IGN] spécification de contenu
[Termes IGN] spécification de produit
[Termes IGN] utilisateur
[Termes IGN] visualisationRésumé : (Auteur) It is common for modern geospatial libraries to contain multiple datasets that cover the same area but differ only in some specific quality attributes (e.g., resolution and precision). This is affecting the concept of content-based geospatial queries, as simple coverage-based query mechanisms (e.g., declaring a specific area of interest) as well as theme-based query mechanisms (e.g., requesting a black and white aerial photo or multispectral satellite imagery) are rendered inadequate to identify and access specific datasets in such collections. In this paper we introduce a novel approach to handle data quality attributes in geospatial queries. Our approach is characterized by the ability to model and learn user preferences, thus establishing user profiles that allow us to customize image queries for improving their functionality in a constantly diversifying geospatial user community. Numéro de notice : A2004-310 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.14358/PERS.70.8.973 En ligne : https://doi.org/10.14358/PERS.70.8.973 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26837
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 8 (August 2004) . - pp 973 - 981[article]Scale and orientation-invariant scene similarity metrics for image queries / A. Stefanidis in International journal of geographical information science IJGIS, vol 16 n° 8 (december 2002)
[article]
Titre : Scale and orientation-invariant scene similarity metrics for image queries Type de document : Article/Communication Auteurs : A. Stefanidis, Auteur ; Peggy Agouris, Auteur ; C. Georgiadis, Auteur ; Michela Bertolotto, Auteur ; James D. Carswell, Auteur Année de publication : 2002 Article en page(s) : pp 749 - 772 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse numérique
[Termes IGN] ligne de base
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] rectangle englobant minimum
[Termes IGN] relation topologique
[Termes IGN] requête (informatique)
[Termes IGN] similitude
[Termes IGN] variation d'échelleRésumé : (Auteur) In this paper, we extend our previous work on shapebased queries to support queries on configurations of image objects. Here we consider spatial reasoning, especially directional and metric object relationships. Existing models for spatial reasoning tend to rely on pre-identified cardinal directions and minimal scale variations, assumptions that cannot be considered as given in our image applications, where orientations and scale may vary substantially, and are often unknown. Accordingly, we have developed the method of varying baselines to identify similarities in direction and distance relations. Our method allows us to evaluate directional similarities without a priori knowledge of cardinal directions, and to compare distance relations even when query scene and database content differ in scale by unknown amounts. We use our method to evaluate similarity between a userdefined query scene and object configurations. Here we present this new method, and discuss its role within a broader image retrieval framework. Numéro de notice : A2002-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810210148552 En ligne : https://doi.org/10.1080/13658810210148552 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22169
in International journal of geographical information science IJGIS > vol 16 n° 8 (december 2002) . - pp 749 - 772[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 079-02081 RAB Revue Centre de documentation En réserve L003 Disponible Integrated spatial data bases / Peggy Agouris (1999)Permalink