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Attributs de texture extraits d'images multispectrales acquises en conditions d'éclairage non contrôlées : application à l'agriculture de précision / Anis Amziane (2022)  

Public Titre : Attributs de texture extraits d'images multispectrales acquises en conditions d'éclairage non contrôlées : application à l'agriculture de précision Type de document : Thèse/HDR Auteurs : Anis Amziane, Auteur ; Ludovic Macaire, Directeur de thèse Editeur : Lille : Université de Lille Année de publication : 2022 Importance : 214 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse pour obtenir le grade de Docteur de l'Université de Lille, spécialité Automatique, Génie Informatique, Traitement du Signal et des Images Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] agriculture de précision [Termes IGN] bande spectrale [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection automatique [Termes IGN] éclairage [Termes IGN] exitance spectrale [Termes IGN] extraction de la végétation [Termes IGN] rayonnement proche infrarouge [Termes IGN] reconnaissance d'objets [Termes IGN] réflectance végétale [Termes IGN] signature spectrale Index. décimale : THESE Thèses et HDR Résumé : (auteur) The main objective of this work is to develop an automatic recognition system of crop and weed plants in field conditions. In Chapter 2 we describe the formation of multispectral radiance images under the Lambertian surface assumption and the different devices that can be used to acquire such images. We then provide a detailed description of the multispectral camera used in this study. Because radiance multispectral images are acquired under varying illumination, we propose an original multispectral image formation model that takes the variation of illumination conditions into account. In chapter 3, we estimate the reflectance as an illumination-invariant spectral signature. First, we present state-of-the-art methods that can be used to estimate the reflectance from multispectral images. We then introduce the reference state-of-the-art method for reflectance estimation and de- scribe our proposed method for reflectance estimation under varying illumination. Chapter 4 focuses on estimated reflectance assessment. The quality of reflectance estimated by our method is evaluated against state-of-the-art methods, and its contribution to supervised crop/weed recognition is demonstrated. Chapter 5 addresses the dimension reduction issue. The acquired multispectral images are composed of a high number of spectral channels, whose analysis is memory and time consuming. Moreover, spectral bands associated to these channels may be redundant or contain highly correlated spectral information. Therefore, we select the best spectral bands for crop/weed classification and use them to specify a camera suited for crop/weed recognition.Chapter 6 deals with the problem of spatio-spectral feature extraction from multispectral images. We propose an approach that extracts both spatial and spectral information at reduced computation costs based on a CNN. Its contribution to crop/weed recognition is demonstrated. Note de contenu : 1- Introduction 2- Multispectral imaging 3- Reflectance estimation 4- Reflectance estimation assessment 5- dimension reduction 6- Raw textures features for crop/weed recognition Conclusion Numéro de notice : 24102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Organisme de stage : Laboratoire Cristal (Lille) DOI : sans En ligne : https://www.theses.fr/2022ULILB020 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102577

Robustness of visual SLAM techniques to light changing conditions / Xi Wang (2022)  

Public Titre : Robustness of visual SLAM techniques to light changing conditions : Influence of contrasted local features, multi-planar representations and multimodal image analysis Type de document : Thèse/HDR Auteurs : Xi Wang, Auteur ; Eric Marchand, Directeur de thèse Editeur : Rennes : Université de Rennes 1 Année de publication : 2022 Importance : 153 p. Format : 21 x 30 cm Note générale : bibliographie Thèse de Doctorat de l'Université de Rennes 1, Spécialité Informatique Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] cartographie et localisation simultanées [Termes IGN] éclairage [Termes IGN] estimation de pose [Termes IGN] information sémantique [Termes IGN] primitive géométrique [Termes IGN] programmation linéaire [Termes IGN] robotique [Termes IGN] vision par ordinateur Index. décimale : THESE Thèses et HDR Résumé : (auteur) The SLAM (Simultaneous Localization And Mapping) technique concentrates on localizing and recovering the environment in a simultaneous way and is one of the core functionalities of many industrial products such as augmented reality, where the device poses should be tracked in real-time; autonomous driving, where one needs to localize the vehicle in a pre-generated map or unknown environment; and even modern filmmaking workflow, where the relative camera position and orientation are critical for post-processing or real-time prevising for directors and actors to visualise the visual effects on the stage. Multiple difficulties in different levels can influence the final performance of robot agents’s SLAM task, as the pipeline is long and complicated from the real world physics to the required information such as agent poses and 3-D map, which help us visualize colourful graphics scenes in AR devices or make hard decisions on the highway for autonomous driving. Many solutions are proposed for addressing each problem, respectively, with the means from classic statistic probability models to the modern data-driven deep neural network. However, the quest of improving the robot’s robustness under dynamic and complicated environments perisists and becomes more and more significant and active for nowadays robotics research. The need for improving the robustness of robot agents is imminent and regarded as one of most imperative factors for deploying robots ubiquitously in our daily life. Under this context, this thesis tries to address a small drop in the ocean of the problem of SLAM robustness, yet in a very systematic view: we try to break down the SLAM system into different and inter-influential modules. Then use the concept of "divide and conquer" for answering possible questions within each module and wishing to contribute to the community and help improve the robustness of SLAM systems under complicated conditions. With the above objectives, the contributions of the thesis are stated as follows for tackling the robustness problem from multiple angles: 1) From the image feature angle, we proposed a multiple layered image structure for improving the performance of traditional local image features under extreme conditions. Furthermore, an optimization method on linear searching and mutual information assisted convex optimization are designed for tuning the optimal parameters with the proposed structure; 2) From the geometric primitive angle, we proposed a relative pose estimation and SLAM framework under the multiple planar assumption, by keypoint feature-based and template tracker based methods, respectively. We tried to achieve better performance of mapping and tracking simultaneously with the help of a more general planar assumption. 3) From the angle of relocalization of the SLAM system, the idea is to recover the already passed locations of the robot agent for lowering the overall estimation error or when the robot is in lost status. We proposed a binary graph structure for embedding spatial information and heterogeneous data formats such as depth image, semantic information etc. The proposed method enables robotics SLAM systems to relocalize themselves with a higher success rate even under different lighting, weather and seasonal conditions. Note de contenu : 1- Introduction 2- Résumé 3- Background on visual SLAM techniques 4- Related work 5- Organisation 6- Multiple layers image 7- Multi-planar relative pose estimation via superpixel 8- TT-SLAM 9- Binary graph descriptor for robust relocalization on heterogeneous data Conclusion Numéro de notice : 24074 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique : Rennes 1 : 2022 Organisme de stage : IRISA DOI : sans En ligne : https://www.theses.fr/2022REN1S022 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102162

Binary space partitioning visibility tree for polygonal and environment light rendering / Hiroki Okuno in The Visual Computer, vol 37 n° 9 - 11 (September 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 9 - 11 (September 2021) . - pp 2499 - 2511 Titre : Binary space partitioning visibility tree for polygonal and environment light rendering Type de document : Article/Communication Auteurs : Hiroki Okuno, Auteur ; Kei Iwasaki, Auteur Année de publication : 2021 Article en page(s) : pp 2499 - 2511 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] arbre BSP [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] éclairage [Termes IGN] éclairement lumineux [Termes IGN] équation intégrale [Termes IGN] intensité lumineuse [Termes IGN] ombre [Termes IGN] polygone [Termes IGN] réflectance [Termes IGN] visibilité (optique) Résumé : (auteur) In this paper, we present a geometric approach to render shadows for physically based materials under polygonal light sources. Direct illumination calculation from a polygonal light source involves the triple product integral of the lighting, the bidirectional reflectance distribution function (BRDF), and the visibility function over the polygonal domain, which is computation intensive. To achieve real-time performance, work on polygonal light shading exploits analytical solutions of boundary integrals along the edges of the polygonal light at the cost of lacking shadowing effects. We introduce a hierarchical representation for the precomputed visibility function to retain the merits of closed-form solutions for boundary integrals. Our method subdivides the polygonal light into a set of polygons visible from a point to be shaded. Experimental results show that our method can render complex shadows with a GGX microfacet BRDF from polygonal light sources at interactive frame rates. In addition, our visibility representation can be easily incorporated into environment lighting. Numéro de notice : A2021-644 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-021-02181-8 Date de publication en ligne : 14/06/2021 En ligne : https://doi.org/10.1007/s00371-021-02181-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98345 [article]

Background segmentation in multicolored illumination environments / Nikolas Ladas in The Visual Computer, vol 37 n° 8 (August 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 8 (August 2021) . - pp 2221 - 2233 Titre : Background segmentation in multicolored illumination environments Type de document : Article/Communication Auteurs : Nikolas Ladas, Auteur ; Paris Kaimakis, Auteur ; Yiorgos Chrysanthou, Auteur Année de publication : 2021 Article en page(s) : pp 2221 - 2233 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification pixellaire [Termes IGN] détection d'ombre [Termes IGN] éclairage [Termes IGN] éclairement lumineux [Termes IGN] modèle stochastique [Termes IGN] objectif grand angulaire [Termes IGN] réflectance [Termes IGN] segmentation d'image Résumé : (auteur) We present an algorithm for the segmentation of images into background and foreground regions. The proposed algorithm utilizes a physically based formulation of scene appearance which explicitly models the formation of shadows originating from color light sources. This formulation enables a probabilistic model to distinguish between shadows and foreground objects in challenging images. A key component of the proposed method is an algorithm for estimating the illumination arriving at the scene. We evaluate our algorithm using synthetic and real-world data and show that the proposed method performs favorably against other commonly used segmentation methods. Numéro de notice : A2021-596 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01981-8 Date de publication en ligne : 06/10/2020 En ligne : https://doi.org/10.1007/s00371-020-01981-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98225 [article]

Leveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 26 - 40 Titre : Leveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction Type de document : Article/Communication Auteurs : Qing Zhu, Auteur ; Zhendong Wang, Auteur ; Han Hu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 26 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] appariement d'images [Termes IGN] appariement de points [Termes IGN] éclairage [Termes IGN] image aérienne [Termes IGN] image terrestre [Termes IGN] maillage [Termes IGN] milieu urbain [Termes IGN] modèle stéréoscopique [Termes IGN] séparateur à vaste marge [Termes IGN] valeur aberrante Résumé : (auteur) Integration of aerial and ground images has been proved as an efficient approach to enhance the surface reconstruction in urban environments. However, as the first step, the feature point matching between aerial and ground images is remarkably difficult, due to the large differences in viewpoint and illumination conditions. Previous studies based on geometry-aware image rectification have alleviated this problem, but the performance and convenience of this strategy are still limited by several flaws, e.g. quadratic image pairs, segregated extraction of descriptors and occlusions. To address these problems, we propose a novel approach: leveraging photogrammetric mesh models for aerial-ground image matching. The methods have linear time complexity with regard to the number of images. It explicitly handles low overlap using multi-view images. The proposed methods can be directly injected into off-the-shelf structure-from-motion (SFM) and multi-view stereo (MVS) solutions. First, aerial and ground images are reconstructed separately and initially co-registered through weak georeferencing data. Second, aerial models are rendered to the initial ground views, in which color, depth and normal images are obtained. Then, feature matching between synthesized and ground images are conducted through descriptor searching and geometry-constrained outlier removal. Finally, oriented 3D patches are formulated using the synthesized depth and normal images and the correspondences are propagated to the aerial views through patch-based matching. Experimental evaluations using five datasets reveal satisfactory performance of the proposed methods in aerial-ground image matching, which succeeds in all of the ten challenging pairs compared to only three for the second best. In addition, incorporation of existing SFM and MVS solutions enables more complete reconstruction results, with better internal stability. Numéro de notice : A2020-351 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.024 Date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.024 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95234 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2020083	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2020082	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

An Illumination Insensitive descriptor combining the CSLBP features for street view images in augmented reality: experimental studies / Zejun Xiang in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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Fusion d'approches photométriques et géométriques pour la création de modèles 3D / Jean Mélou (2020)  

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Handbook on advances in remote sensing and geographic information systems / Margarita N. Favorskaya (2017)

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A bright idea: testing the feasibility of positionning using ambient light / J. Liu in GPS world, vol 25 n° 11 (novembre 2014)  

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Synthèse d'images géographiques / F. Sillion (2002)

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Acquisition & visualisation des images / A. Marion (1997)

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Photogrammétrie terrestre et archéologie / Y. Manginot (1997)

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La colorimétrie / Y. Dordet (1994)

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Tome 2. Color measurement / F. Grum (1980)

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Le girasol, hauteur et azimut du soleil pour toutes les latitudes / Centre de recherches method. d'architecture & d'amenag (1979)

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