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Efficiently annotating object images with absolute size information using mobile devices / Martin Hofmann in International journal of computer vision, vol 127 n° 2 (February 2019)  

Public [article]  inInternational journal of computer vision > vol 127 n° 2 (February 2019) . - pp 207 - 224 Titre : Efficiently annotating object images with absolute size information using mobile devices Type de document : Article/Communication Auteurs : Martin Hofmann, Auteur ; Marco Seeland, Auteur ; Patrick Mäder, Auteur Année de publication : 2019 Article en page(s) : pp 207 - 224 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] appareil portable [Termes descripteurs IGN] appariement automatique [Termes descripteurs IGN] image numérique [Termes descripteurs IGN] longueur focale Résumé : (Auteur) The projection of a real world scenery to a planar image sensor inherits the loss of information about the 3D structure as well as the absolute dimensions of the scene. For image analysis and object classification tasks, however, absolute size information can make results more accurate. Today, the creation of size annotated image datasets is effort intensive and typically requires measurement equipment not available to public image contributors. In this paper, we propose an effective annotation method that utilizes the camera within smart mobile devices to capture the missing size information along with the image. The approach builds on the fact that with a camera, calibrated to a specific object distance, lengths can be measured in the object’s plane. We use the camera’s minimum focus distance as calibration distance and propose an adaptive feature matching process for precise computation of the scale change between two images facilitating measurements on larger object distances. Eventually, the measured object is segmented and its size information is annotated for later analysis. A user study showed that humans are able to retrieve the calibration distance with a low variance. The proposed approach facilitates a measurement accuracy comparable to manual measurement with a ruler and outperforms state-of-the-art methods in terms of accuracy and repeatability. Consequently, the proposed method allows in-situ size annotation of objects in images without the need for additional equipment or an artificial reference object in the scene. Numéro de notice : A2018-600 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-018-1093-3 date de publication en ligne : 24/05/2018 En ligne : https://doi.org/10.1007/s11263-018-1093-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92527 [article]

Trajectory-based place-recognition for efficient large scale localization / Simon Lynen in International journal of computer vision, vol 124 n° 1 (August 2017)  

Public [article]  inInternational journal of computer vision > vol 124 n° 1 (August 2017) . - pp 49 – 64 Titre : Trajectory-based place-recognition for efficient large scale localization Type de document : Article/Communication Auteurs : Simon Lynen, Auteur ; Michael Bosse, Auteur ; Roland Siegwart, Auteur Année de publication : 2017 Article en page(s) : pp 49 – 64 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] alignement multiple semi-dirigé [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] appariement automatique [Termes descripteurs IGN] lieu géométrique [Termes descripteurs IGN] précision de localisation [Termes descripteurs IGN] reconnaissance automatique Résumé : (auteur) Place recognition is a core competency for any visual simultaneous localization and mapping system. Identifying previously visited places enables the creation of globally accurate maps, robust relocalization, and multi-user mapping. To match one place to another, most state-of-the-art approaches must decide a priori what constitutes a place, often in terms of how many consecutive views should overlap, or how many consecutive images should be considered together. Unfortunately, such threshold dependencies limit their generality to different types of scenes. In this paper, we present a placeless place recognition algorithm using a novel match-density estimation technique that avoids heuristically discretizing the space. Instead, our approach considers place recognition as a problem of continuous matching between image streams, automatically discovering regions of high match density that represent overlapping trajectory segments. The algorithm uses well-studied statistical tests to identify the relevant matching regions which are subsequently passed to an absolute pose algorithm to recover the geometric alignment. We demonstrate the efficiency and accuracy of our methodology on three outdoor sequences, including a comprehensive evaluation against ground-truth from publicly available datasets that shows our approach outperforms several state-of-the-art algorithms for place recognition. Furthermore we compare our overall algorithm to the currently best performing system for global localization and show how we outperform the approach on challenging indoor and outdoor datasets. Numéro de notice : A2017-399 Thématique : IMAGERIE Nature : Article En ligne : https://doi.org/10.1007/s11263-016-0947-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85941 [article]

A method for matching crowd-sourced and authoritative geospatial data / Heshan Du in Transactions in GIS, vol 21 n° 2 (April 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 2 (April 2017) . - pp 406 – 427 Titre : A method for matching crowd-sourced and authoritative geospatial data Type de document : Article/Communication Auteurs : Heshan Du, Auteur ; Natasha Alechina, Auteur ; Michael Jackson, Auteur ; Glen Hart, Auteur Année de publication : 2017 Article en page(s) : pp 406 – 427 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes descripteurs IGN] appariement automatique [Termes descripteurs IGN] appariement de données localisées [Termes descripteurs IGN] données ouvertes [Termes descripteurs IGN] France (administrative) [Termes descripteurs IGN] géomatique web [Termes descripteurs IGN] Grande-Bretagne [Termes descripteurs IGN] infrastructure nationale des données localisées [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] organisme cartographique national Résumé : (auteur) A method for matching crowd-sourced and authoritative geospatial data is presented. A level of tolerance is defined as an input parameter as some difference in the geometry representation of a spatial object is to be expected. The method generates matches between spatial objects using location information and lexical information, such as names and types, and verifies consistency of matches using reasoning in qualitative spatial and description logic. We test the method by matching geospatial data from OpenStreetMap and the national mapping agencies of Great Britain and France. We also analyze how the level of tolerance affects the precision and recall of matching results for the same geographic area using 12 different levels of tolerance within a range of 1 to 80 m. The generated matches show potential in helping enrich and update geospatial data. Numéro de notice : A2017-168 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1111/tgis.12210 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84702 [article]

Two heads are better than one / Brian Curtiss in GEO: Geoconnexion international, vol 15 n° 8 (September 2016)

Public [article]  inGEO: Geoconnexion international > vol 15 n° 8 (September 2016) . - pp 33 - 37 Titre : Two heads are better than one Type de document : Article/Communication Auteurs : Brian Curtiss, Auteur Année de publication : 2016 Article en page(s) : pp 33 - 37 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement automatique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] spectroradiométrie Résumé : (éditeur) Using linked spectroradiometers enables far better collection of field reflectance spectra, to improve the matching of remote sensed imagery.Brian Curtiss shows how it can be done Numéro de notice : A2016-662 Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81893 [article]

Geometrical consistency voting strategy for outlier detection in image matching / Luping Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 7 (juillet 2016) . - pp 559 - 570 Titre : Geometrical consistency voting strategy for outlier detection in image matching Type de document : Article/Communication Auteurs : Luping Lu, Auteur ; Yong Zhang, Auteur ; Pengjie Tao, Auteur Année de publication : 2016 Article en page(s) : pp 559 - 570 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement automatique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] cohérence géométrique [Termes descripteurs IGN] détection d'anomalie [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] transformation de Hough [Termes descripteurs IGN] valeur aberrante Résumé : (Auteur) False matches in tie-point image matching are common. This paper introduces a straightforward and effective prepossessing method to reject false matches from initial matches. The method is based on the idea of Hough transform using only two geometrical consistency parameters, namely, the scale parameter and the rotation parameter between two images. A weighted voting strategy is employed, and it can further improve the robustness of the algorithm. The method can handle a large rate of outliers and produce more robust matches with low complexity. No assumptions with regard to the relative pose between two images are necessary, and large perspective deformation can be handled as well. Experiments with ground reference data show that the algorithm works effectively even when the ratio of inliers is below 10 percent. In these data, the ratio of inliers can be improved from 5 percent to 40 percent on average. Numéro de notice : A2016-517 Thématique : IMAGERIE Nature : Article En ligne : http://dx.doi.org/10.14358/PERS.82.7.559 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81588 [article]

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