Photogrammetric record / Remote sensing and photogrammetry society . vol 22 n° 120Paru le : 01/12/2007 ISBN/ISSN/EAN : 0031-868X |
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Ajouter le résultat dans votre panierImportant considerations for cranofacial mapping using laser scanners / Z. Majid in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)
[article]
Titre : Important considerations for cranofacial mapping using laser scanners Type de document : Article/Communication Auteurs : Z. Majid, Auteur ; A.K. Chong, Auteur ; Halim Setan, Auteur Année de publication : 2007 Article en page(s) : pp 290 - 308 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] médecine humaine
[Termes IGN] restitution
[Termes IGN] télémètre laser terrestre
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) The use of a laser scanning system for human craniofacial mapping has gained considerable interest recently as it offers a non-contact method which is very efficient in capturing a vast amount of accurate spatial data. Nonetheless, there is a need for a thorough evaluation to identify the important technical factors which may affect the accuracy of the system. This paper discusses the tests and the results of an evaluation of the Minolta VI-910 3D laser scanning system used to capture craniofacial surface data. The research shows that the factors to consider for craniofacial mapping are: scan distance, camera focal length, laser beam intensity, scanning resolution, convergence angle and number of overlapping scans. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2007-566 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2007.00449.x En ligne : https://doi.org/10.1111/j.1477-9730.2007.00449.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28929
in Photogrammetric record > vol 22 n° 120 (December 2007 - February 2008) . - pp 290 - 308[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-07041 Revue Centre de documentation Revues en salle Disponible Rational function model for sensor orientation of IRS-P6 LISS-4 imagery / V. Nagasubramanian in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)
[article]
Titre : Rational function model for sensor orientation of IRS-P6 LISS-4 imagery Type de document : Article/Communication Auteurs : V. Nagasubramanian, Auteur ; P. Radhadevi, Auteur ; R. Ramachandran, Auteur ; R. Krishnan, Auteur Année de publication : 2007 Article en page(s) : pp 309 - 320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] géométrie de l'image
[Termes IGN] géoréférencement direct
[Termes IGN] image IRS-LISS
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] orientation du capteur
[Termes IGN] point d'appuiRésumé : (Auteur) This paper explores the application of a rational function model (RFM) as a replacement sensor model for IRS-P6 LISS-4 imagery. The rational polynomial coefficients (RPCs), initially generated using a rigorous sensor model (RSM) through direct georeferencing, are bias-compensated with a minimum number of ground control points and are used for various photogrammetric applications such as digital elevation model and ortho-image generation. The performance of RFM and RSM is compared in the sensor modelling of LISS-4 imagery over long strips. Results show that accuracies achieved using RFM are within 1 pixel (worst case) of the accuracies derived using RSM. Error variation as a function of the number of quasi-control points (anchor points) used for RFM fitting as well as model errors with respect to the length of the image strip are analysed. System-level accuracy does not deteriorate when the RFM is fitted up to a length of 1200 km. Absolute positioning accuracy of 1·5 pixels (~9 m) is achieved from bias-compensated RPCs. The results demonstrate the potential of RFM as a replacement sensor model. This allows standardisation of product generation packages to handle multiple sensors. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2007-567 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2007.00447.x En ligne : https://doi.org/10.1111/j.1477-9730.2007.00447.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28930
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Code-barres Cote Support Localisation Section Disponibilité 106-07041 Revue Centre de documentation Revues en salle Disponible A sub-pixel location method for interest points by means of the Harris interest strength / Q. Zhu in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)
[article]
Titre : A sub-pixel location method for interest points by means of the Harris interest strength Type de document : Article/Communication Auteurs : Q. Zhu, Auteur ; B. Wu, Auteur Année de publication : 2007 Article en page(s) : pp 321 - 335 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] algorithme de Gauss
[Termes IGN] analyse infrapixellaire
[Termes IGN] géoréférencement
[Termes IGN] méthode des moindres carrés
[Termes IGN] niveau de gris (image)
[Termes IGN] point d'intérêt
[Termes IGN] reconstruction 3DRésumé : (Auteur) The sub-pixel location of interest points is one of the most important tasks in refined image-based 3D reconstruction in digital photogrammetry. The interest point detectors based on the Harris principles are generally used for stereoscopic image matching and subsequent 3D reconstruction. However, the locations of the interest points detected in this way can only be obtained to 1 pixel accuracy. The Harris detector has the following characteristics: (1) the Harris interest strength, which denotes the distinctiveness of an interest point, is a grey scale descriptor which computes the gradient at each sample point in a region around the point, and (2) the Harris interest strengths of the pixels in a template window centred on the interest point exhibit an approximately paraboloid distribution. This paper proposes a precise location method to improve the precision of the interest points on the basis of these characteristics of the Harris interest strength. Firstly, a least squares fit of a paraboloid function to the image grey scale surface using the Harris interest strength is designed in a template window and a Gaussian-distance algorithm is employed to determine the weight. Then, the precise coordinates of this interest point are obtained by calculating the extremities of the fitting surface. The location accuracy of this method is studied both from the theoretical and the practical point of view. Experimental analysis is illustrated with synthetic images as well as actual images, which yielded a location accuracy of 0·15 pixels. Furthermore, experimental results also indicate that this method has the desired anti-image-noise and efficiency characteristics. Numéro de notice : A2007-568 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2007.00450.x En ligne : https://doi.org/10.1111/j.1477-9730.2007.00450.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28931
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Code-barres Cote Support Localisation Section Disponibilité 106-07041 Revue Centre de documentation Revues en salle Disponible Visibility prediction based on artificial neural networks used in automatic network design / M. Saadatseresht in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)
[article]
Titre : Visibility prediction based on artificial neural networks used in automatic network design Type de document : Article/Communication Auteurs : M. Saadatseresht, Auteur ; Masood Varshosaz, Auteur Année de publication : 2007 Article en page(s) : pp 336 - 355 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] apprentissage automatique
[Termes IGN] incertitude des données
[Termes IGN] photogrammétrie terrestre
[Termes IGN] réseau neuronal artificiel
[Termes IGN] visibilitéRésumé : (Auteur) Automatic design of photogrammetric networks is a complex task for which the visibility and quality constraints need to be both modelled and satisfied simultaneously. The task becomes even more complex when measurements are carried out for the first time on a large and/or complex object surrounded by multiple obstructions in a confined workspace. In this situation, automatic visibility prediction of a target point becomes an extremely difficult task. The visibility information inherent within the initial photogrammetric network can be used to solve this problem. However, this introduces some uncertainty into the prediction result because of the incompleteness of the visibility information. In a previous study, the authors developed an analytical deterministic method, visibility uncertainty prediction (VUP), that used ‘‘visibility spheres’’ to predict the visibility of target points. This paper investigates the use of artificial neural networks (ANNs) in visibility prediction, and presents a new technique, ANN-based visibility uncertainty prediction (AVUP), that works by training a feed-forward multi-layer ANN. The visibility data for this network is extracted from the initial photogrammetric network. Once trained, the network can be used to predict the visibility of any target point from a potential camera station. Various experiments were carried out to evaluate the proposed technique. The results showed that, compared to the previous deterministic method, it is more accurate and has a lower computational cost. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2007-569 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2007.00454.x En ligne : https://doi.org/10.1111/j.1477-9730.2007.00454.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28932
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Code-barres Cote Support Localisation Section Disponibilité 106-07041 Revue Centre de documentation Revues en salle Disponible