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Summarizing large scale 3D mesh for urban navigation / Imeen Ben Salah in Robotics and autonomous systems, vol 152 (June 2022)  

Public [article]  inRobotics and autonomous systems > vol 152 (June 2022) . - n° 104037 Titre : Summarizing large scale 3D mesh for urban navigation Type de document : Article/Communication Auteurs : Imeen Ben Salah, Auteur ; Sébastien Kramm, Auteur ; Cédric Demonceaux, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104037 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme ICP [Termes IGN] carte en 3D [Termes IGN] données lidar [Termes IGN] entropie [Termes IGN] image hémisphérique [Termes IGN] image RVB [Termes IGN] information sémantique [Termes IGN] localisation basée vision [Termes IGN] maillage [Termes IGN] navigation autonome [Termes IGN] précision géométrique (imagerie) [Termes IGN] précision radiométrique [Termes IGN] profondeur [Termes IGN] Rouen [Termes IGN] saillance [Termes IGN] zone urbaine Résumé : (auteur) Cameras have become increasingly common in vehicles, smartphones, and advanced driver assistance systems. The areas of application of these cameras in the world of intelligent transportation systems are becoming more and more varied: pedestrian detection, line crossing detection, navigation, …A major area of research currently focuses on mapping that is essential for localization and navigation. However, this step generates an important problem of memory management. Indeed, the memory space required to accommodate the map of a small city is measured in tens gigabytes. In addition, several providers today are competing to produce High-Definition (HD) maps. These maps offer a rich and detailed representation of the environment for highly accurate localization. However, they require a large storage capacity and high transmission and update costs. To overcome these problems, we propose a solution to summarize this type of map by reducing the size while maintaining the relevance of the data for navigation based on vision only. The summary consists in a set of spherical images augmented by depth and semantic information and allowing to keep the same level of visibility in every directions. These spheres are used as landmarks to offer guidance information to a distant agent. They then have to guarantee, at a lower cost, a good level of precision and speed during navigation. Some experiments on real data demonstrate the feasibility for obtaining a summarized map while maintaining a localization with interesting performances. Numéro de notice : A2022-290 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.robot.2022.104037 Date de publication en ligne : 03/02/2022 En ligne : https://doi.org/10.1016/j.robot.2022.104037 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100335 [article]

GeoRec: Geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes / Linxi Huan in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 301 - 314 Titre : GeoRec: Geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes Type de document : Article/Communication Auteurs : Linxi Huan, Auteur ; Xianwei Zheng, Auteur ; Jianya Gong, Auteur Année de publication : 2022 Article en page(s) : pp 301 - 314 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] données localisées 3D [Termes IGN] géométrie [Termes IGN] image RVB [Termes IGN] maillage [Termes IGN] modélisation sémantique [Termes IGN] objet 3D [Termes IGN] reconstruction 3D [Termes IGN] reconstruction d'objet [Termes IGN] scène intérieure Résumé : (auteur) Semantic indoor 3D modeling with multi-task deep neural networks is an efficient and low-cost way for reconstructing an indoor scene with geometrically complete room structure and semantic 3D individuals. Challenged by the complexity and clutter of indoor scenarios, the semantic reconstruction quality of current methods is still limited by the insufficient exploration and learning of 3D geometry information. To this end, this paper proposes an end-to-end multi-task neural network for geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes (termed as GeoRec). In the proposed GeoRec, we build a geometry extractor that can effectively learn geometry-enhanced feature representation from depth data, to improve the estimation accuracy of layout, camera pose and 3D object bounding boxes. We also introduce a novel object mesh generator that strengthens the reconstruction robustness of GeoRec to indoor occlusion with geometry-enhanced implicit shape embedding. With the parsed scene semantics and geometries, the proposed GeoRec reconstructs an indoor scene by placing reconstructed object mesh models with 3D object detection results in the estimated layout cuboid. Extensive experiments conducted on two benchmark datasets show that the proposed GeoRec yields outstanding performance with mean chamfer distance error for object reconstruction on the challenging Pix3D dataset, 70.45% mAP for 3D object detection and 77.1% 3D mIoU for layout estimation on the commonly-used SUN RGB-D dataset. Especially, the mesh reconstruction sub-network of GeoRec trained on Pix3D can be directly transferred to SUN RGB-D without any fine-tuning, manifesting a high generalization ability. Numéro de notice : A2022-235 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2022.02.014 Date de publication en ligne : 03/03/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.02.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100139 [article]

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Deep-learning-based multispectral image reconstruction from single natural color RGB image - Enhancing UAV-based phenotyping / Jiangsan Zhao in Remote sensing, vol 14 n° 5 (March-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 5 (March-1 2022) . - n° 1272; Titre : Deep-learning-based multispectral image reconstruction from single natural color RGB image - Enhancing UAV-based phenotyping Type de document : Article/Communication Auteurs : Jiangsan Zhao, Auteur ; Ajay Kumar, Auteur ; Balaji Naik Banoth, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1272; Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] agriculture de précision [Termes IGN] apprentissage profond [Termes IGN] erreur absolue [Termes IGN] image multibande [Termes IGN] image RVB [Termes IGN] Inde [Termes IGN] phénologie [Termes IGN] reconstruction d'image Résumé : (auteur) Multispectral images (MSIs) are valuable for precision agriculture due to the extra spectral information acquired compared to natural color RGB (ncRGB) images. In this paper, we thus aim to generate high spatial MSIs through a robust, deep-learning-based reconstruction method using ncRGB images. Using the data from the agronomic research trial for maize and breeding research trial for rice, we first reproduced ncRGB images from MSIs through a rendering model, Model-True to natural color image (Model-TN), which was built using a benchmark hyperspectral image dataset. Subsequently, an MSI reconstruction model, Model-Natural color to Multispectral image (Model-NM), was trained based on prepared ncRGB (ncRGB-Con) images and MSI pairs, ensuring the model can use widely available ncRGB images as input. The integrated loss function of mean relative absolute error (MRAEloss) and spectral information divergence (SIDloss) were most effective during the building of both models, while models using the MRAEloss function were more robust towards variability between growing seasons and species. The reliability of the reconstructed MSIs was demonstrated by high coefficients of determination compared to ground truth values, using the Normalized Difference Vegetation Index (NDVI) as an example. The advantages of using “reconstructed” NDVI over Triangular Greenness Index (TGI), as calculated directly from RGB images, were illustrated by their higher capabilities in differentiating three levels of irrigation treatments on maize plants. This study emphasizes that the performance of MSI reconstruction models could benefit from an optimized loss function and the intermediate step of ncRGB image preparation. The ability of the developed models to reconstruct high-quality MSIs from low-cost ncRGB images will, in particular, promote the application for plant phenotyping in precision agriculture. Numéro de notice : A2022-210 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14051272 Date de publication en ligne : 05/03/2022 En ligne : https://doi.org/10.3390/rs14051272 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100033 [article]

Effective CBIR based on hybrid image features and multilevel approach / D. Latha in Multimedia tools and applications, vol inconnu (March 2022)  

Public [article]  inMultimedia tools and applications > vol inconnu (March 2022) . - pp Titre : Effective CBIR based on hybrid image features and multilevel approach Type de document : Article/Communication Auteurs : D. Latha, Auteur ; A. Geetha, Auteur Année de publication : 2022 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données d'images [Termes IGN] écart type [Termes IGN] espace colorimétrique [Termes IGN] image en couleur [Termes IGN] image RVB [Termes IGN] matrice de co-occurrence [Termes IGN] motif binaire local [Termes IGN] niveau de gris (image) [Termes IGN] observation multiniveaux [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] saturation de la couleur [Termes IGN] texture d'image [Termes IGN] transformation intensité-teinte-saturation Résumé : (auteur) Content based image retrieval (CBIR) process can retrieve images by matching its feature set values. The proposed novel CBIR methodology called Effective CBIR based on hybrid image features and multilevel approach (CBIR_LTP_GLCM) integrates the hybrid features such as color features and texture features, along with multilevel approach. The color features such as mean and standard deviation are adopted in the proposed method to represent the global color properties of an image. This method manipulates the color input-image by processing the Hue, Saturation and Value channels of the HSV color space. This novel work is enriched with the image feature derived from Local Ternary Pattern (LTP) in addition with GLCM. So, the proposed method CBIR_LTP_GLCM is potentially charged with meaningful modifications travelling with color image manipulation and extended image retrieval accuracy with the aid of multilevel approach. The proposed methodology is experimentally compared with the existing recent CBIR versions by using the standard database such as Corel-1 k, and a user contributed database named DB_VEG. Numéro de notice : A2022-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s11042-022-12588-7 Date de publication en ligne : 30/03/2022 En ligne : https://doi.org/10.1007/s11042-022-12588-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100337 [article]

Vegetation index and dynamics / Eusebio Cano Carmona (2022)  

Public Titre : Vegetation index and dynamics Type de document : Monographie Auteurs : Eusebio Cano Carmona, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2022 Importance : 350 p. ISBN/ISSN/EAN : 978-1-83969-385-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spatiale [Termes IGN] analyse spectrale [Termes IGN] Autocad Map [Termes IGN] carte de la végétation [Termes IGN] changement d'utilisation du sol [Termes IGN] Colombie [Termes IGN] couvert forestier [Termes IGN] dynamique de la végétation [Termes IGN] écosystème urbain [Termes IGN] flore endémique [Termes IGN] image aérienne [Termes IGN] image captée par drone [Termes IGN] image RVB [Termes IGN] Inde [Termes IGN] indice de diversité [Termes IGN] indice de végétation [Termes IGN] milieu urbain [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] outil d'aide à la décision [Termes IGN] Pakistan [Termes IGN] pédologie locale [Termes IGN] Pennsylvanie (Etats-Unis) [Termes IGN] Pinus sylvestris [Termes IGN] système d'information géographique [Termes IGN] traitement d'image Index. décimale : 35.41 Applications de télédétection - végétation Résumé : (Editeur) The book contemplates different ways of approaching the study of vegetation as well as the type of indices to be used. However, all the works pursue the same objective: to know and interpret nature from different points of view, either through knowledge of nature in situ or the use of technology and mapping using satellite images. Chapters analyze the ecological parameters that affect vegetation, the species that make up plant communities, and the influence of humans on vegetation. Note de contenu : 1. Introductory Chapter: Methodological Aspects for the Study of Vegetation / Eusebio Cano Carmona, Ricardo Quinto Canas, Ana Cano Ortiz and Carmelo María Musarella 2. Using GIS and the Diversity Indices: A Combined Approach to Woody Plant Diversity in the Urban Landscape / Tuba Gül Doğan and Engin Eroğlu 3. Classical and Modern Remote Mapping Methods for Vegetation Cover / Algimantas Česnulevičius, Artūras Bautrėnas, Linas Bevainis and Donatas Ovodas 4. Assessment of the State of Forest Plant Communities of Scots Pine (Pinus sylvestris L.) in the Conditions of Urban Ecosystems / Elena Runova, Vera Savchenkova, Ekaterina Demina-Moskovskaya and Anastasia Baranenkova 5. Landscape Genetics and Phytogeography of Criollo Avocadoes Persea americana from Northeast Colombia / Clara Inés Saldamando-Benjumea, Gloria Patricia Cañas-Gutiérrez, Jorge Muñoz and Rafael Arango Isaza 6. The Use of NDVI and NDBI to Provide Subsidies to Public Manager’s Decision Making on Maintaining the Thermal Comfort in Urban Areas / Arthur Santos, Fernando Santil and Claudionor Silva 7. Detailed Investigation of Spectral Vegetation Indices for Fine Field-Scale Phenotyping / Maria Polivova and Anna Brook 8. Predictive Models for Reforestation and Agricultural Reclamation: A Clearfield County, Pennsylvania Case Study / Zhi Yue and Jon Bryan Burley 9. Dynamic-Catenal Phytosociology for Evaluating Vegetation / Sara del Río, Raquel Alonso-Redondo, Alejandro González-Pérez, Aitor Álvarez-Santacoloma, Giovanni Breogán Ferreiro Lera and Ángel Penas 10. Germination and Seedling Growth of Entandrophragma bussei Harms ex Engl. from Wild Populations / Samora M. Andrew, Siwa A. Kombo and Shabani A.O. Chamshama 11. Spatial Dynamics of Forest Cover and Land Use Changes in the Western Himalayas of Pakistan / Amjad ur Rahman, Esra Gürbüz, Semih Ekercin and Shujaul Mulk Khan 12. Understanding Past and Present Vegetation Dynamics Using the Palynological Approach: An Introductory Discourse / Sylvester Onoriode Obigba 13. Forest Vegetation and Dynamics Studies in India / Madan Prasad Singh, Manohara Tattekere Nanjappa, Sukumar Raman, Suresh Hebbalalu Satyanatayana, Ayyappan Narayanan, Ganesan Renagaian and Sreejith Kalpuzha Ashtamoorthy 14. Photosynthetic Antenna Size Regulation as an Essential Mechanism of Higher Plants Acclimation to Biotic and Abiotic Factors: The Role of the Chloroplast Plastoquinone Pool and Hydrogen Peroxide / Maria M. Borisova-Mubarakshina, Ilya A. Naydov, Daria V. Vetoshkina, Marina A. Kozuleva, Daria V. Vilyanen, Natalia N. Rudenko and Boris N. Ivanov 15. Rockbee Repellent Endemic Plant Species of Andaman-Nicobar Archipelago in the Bay of Bengal / Sam Paul Mathew and Raveendranpillai Prakashkumar 16. Evaluating Insects as Bioindicators of the Wetland Environment Quality (Arid Region of Algeria) / Brahimi Djamel, Rahmouni Abdelkader, Brahimi Abdelghani and Mesli Lotfi Numéro de notice : 26797 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87465 Date de publication en ligne : 23/02/2022 En ligne : https://doi.org/10.5772/intechopen.87465 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100059

Building detection with convolutional networks trained with transfer learning / Simon Šanca in Geodetski vestnik, vol 65 n° 4 (December 2021 - February 2022)  

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Feature matching for multi-epoch historical aerial images: A new pipeline feature detection pipeline in open-source MicMac / Lulin Zhang in Blog de la RFPT, sans n° ([17/11/2021])  

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Feature matching for multi-epoch historical aerial images / Lulin Zhang in ISPRS Journal of photogrammetry and remote sensing, Vol 182 (December 2021)    

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A deep multi-modal learning method and a new RGB-depth data set for building roof extraction / Mehdi Khoshboresh Masouleh in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

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CNN-based RGB-D salient object detection: Learn, select, and fuse / Hao Chen in International journal of computer vision, vol 129 n° 7 (July 2021)  

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Remote sensing image colorization using symmetrical multi-scale DCGAN in YUV color space / Min Wu in The Visual Computer, vol 37 n° 7 (July 2021)  

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Semantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)  

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Assessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, PhenoCam) and satellite (MODIS, Sentinel-2) remote sensing / Shangharsha Thapa in Remote sensing, vol 13 n° 8 (April-2 2021)  

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Visual positioning in indoor environments using RGB-D images and improved vector of local aggregated descriptors / Longyu Zhang in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)  

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Multi-level progressive parallel attention guided salient object detection for RGB-D images / Zhengyi Liu in The Visual Computer, vol 37 n° 3 (March 2021)  

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