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Spherically optimized RANSAC aided by an IMU for Fisheye Image Matching / Anbang Liang in Remote sensing, vol 13 n°10 (May 2021)  

Public [article]  inRemote sensing > vol 13 n°10 (May 2021) . - n° 2017 Titre : Spherically optimized RANSAC aided by an IMU for Fisheye Image Matching Type de document : Article/Communication Auteurs : Anbang Liang, Auteur ; Qingquan Li, Auteur ; Zhipeng Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] centrale inertielle [Termes IGN] coordonnées sphériques [Termes IGN] distorsion d'image [Termes IGN] estimation de pose [Termes IGN] étalonnage de chambre métrique [Termes IGN] géométrie épipolaire [Termes IGN] image hémisphérique [Termes IGN] Ransac (algorithme) Résumé : (auteur) Fisheye cameras are widely used in visual localization due to the advantage of the wide field of view. However, the severe distortion in fisheye images lead to feature matching difficulties. This paper proposes an IMU-assisted fisheye image matching method called spherically optimized random sample consensus (So-RANSAC). We converted the putative correspondences into fisheye spherical coordinates and then used an inertial measurement unit (IMU) to provide relative rotation angles to assist fisheye image epipolar constraints and improve the accuracy of pose estimation and mismatch removal. To verify the performance of So-RANSAC, experiments were performed on fisheye images of urban drainage pipes and public data sets. The experimental results showed that So-RANSAC can effectively improve the mismatch removal accuracy, and its performance was superior to the commonly used fisheye image matching methods in various experimental scenarios. Numéro de notice : A2021-416 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13102017 date de publication en ligne : 20/05/2021 En ligne : https://doi.org/10.3390/rs13102017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97757 [article]

The impacts of building orientation on polarimetric orientation angle estimation and model-based decomposition for multilook polarimetric SAR data in urban areas / Hongzhong Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5520 - 5532 Titre : The impacts of building orientation on polarimetric orientation angle estimation and model-based decomposition for multilook polarimetric SAR data in urban areas Type de document : Article/Communication Auteurs : Hongzhong Li, Auteur ; Qingquan Li, Auteur ; Guofeng Wu, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 5520 - 5532 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] angle de visée [Termes IGN] bati [Termes IGN] données polarimétriques [Termes IGN] orientation [Termes IGN] polarimétrie radar [Termes IGN] reconstruction 3D du bâti [Termes IGN] zone urbaine Résumé : (Auteur) Building orientation with respect to the radar look direction has a critical influence on the interpretation of multilook polarimetric synthetic aperture radar (PolSAR) data in urban areas. In this paper, its impacts on polarimetric orientation angle (POA) estimation and model-based decomposition are discussed. The discussion begins with the analysis of the general double-bounce scattering model, of which the characteristics are dependent on the electromagnetic and geometric parameters of the related dihedral structure. Then, for multilook PolSAR data, the polarimetric scattering mechanism in urban areas is modeled by two double-bounce scatterings from two orthogonal dihedral structures. From the model, the impacts of the building orientation on POA estimation can be revealed. With the increase of the building orientation, the POA difference between the two dihedral structures increases gradually, and the feasibility to estimate the building orientation via the estimated POA is reduced dramatically. Upon further analysis, we illustrate the impacts on the model-based decomposition. With the increase of the building orientation, the dominant scattering mechanism labeling technique based on the model-based decompositions will gradually become invalid. Moreover, the processing of POA compensation, which is helpful in reducing the impacts of the building orientation, also becomes invalid when the building orientation increases to a certain value. At last, three L-band data sets of San Francisco acquired by AIRSAR are used to verify the inferences. The experimental results show that, for L-band PolSAR data in urban areas, when the radar look angle is around 45, the threshold of building orientation for the validity of dominant scattering mechanism labeling is about ±3, and for the POA compensation, the threshold is about ±12. Numéro de notice : A2016-904 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2567421 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83099 [article]

Spatiotemporal data model for network time geographic analysis in the era of big data / Bi Yu Chen in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1041 - 1071 Titre : Spatiotemporal data model for network time geographic analysis in the era of big data Type de document : Article/Communication Auteurs : Bi Yu Chen, Auteur ; H. Yuan, Auteur ; Qingquan Li, Auteur Année de publication : 2016 Article en page(s) : pp 1041 - 1071 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données massives [Termes IGN] données spatiotemporelles [Termes IGN] entité géographique [Termes IGN] milieu urbain [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] temps Résumé : (Auteur) There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities. Numéro de notice : A2016-294 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1104317 En ligne : https://doi.org/10.1080/13658816.2015.1104317 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80878 [article]

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A hybrid link-node approach for finding shortest paths in road networks with turn restrictions / Qingquan Li in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 915 - 929 Titre : A hybrid link-node approach for finding shortest paths in road networks with turn restrictions Type de document : Article/Communication Auteurs : Qingquan Li, Auteur ; Bi Yu Chen, Auteur ; Yafei Wang, Auteur ; William H. K. Lam, Auteur Année de publication : 2015 Article en page(s) : pp 915 - 929 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] calcul d'itinéraire [Termes IGN] chemin le plus court (algorithme) [Termes IGN] navigation automobile [Termes IGN] noeud [Termes IGN] requête spatiale [Termes IGN] réseau routier [Termes IGN] restriction d'accès [Termes IGN] traitement de données localisées Résumé : (auteur) Turn restrictions, such as ‘no left turn’ or ‘no U-turn’, are commonly encountered in real road networks. These turn restrictions must be explicitly considered in the shortest path problem and ignoring them may lead to infeasible paths. In the present study, a hybrid link-node Dijkstra's (HLND) algorithm is proposed to exactly solve the shortest path problem in road networks with turn restrictions. A new hybrid link–node labelling approach is devised by using a link–based labelling strategy at restricted nodes with turn restrictions, and a node-based labelling strategy at unrestricted nodes without turn restrictions. Computational results for several real road networks show that the proposed HLND algorithm obtains the same optimal results as the link-based Dijkstra's algorithm, while having a similar computational performance to the classical node-based Dijkstra's algorithm. Numéro de notice : A2016-438 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1111/tgis.12133 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81349 [article]

Gabor feature-based collaborative representation for hyperspectral imagery classification / Sen Jia in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 1118 - 1129 Titre : Gabor feature-based collaborative representation for hyperspectral imagery classification Type de document : Article/Communication Auteurs : Sen Jia, Auteur ; Linlin Shen, Auteur ; Qingquan Li, Auteur Année de publication : 2015 Article en page(s) : pp 1118 - 1129 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification spectrale [Termes IGN] conception collaborative [Termes IGN] état de l'art [Termes IGN] extraction de traits caractéristiques [Termes IGN] filtre de Gabor [Termes IGN] image hyperspectrale [Termes IGN] précision de la classification Résumé : (Auteur) Sparse-representation-based classification (SRC) assigns a test sample to the class with minimum representation error via a sparse linear combination of all the training samples, which has successfully been applied to several pattern recognition problems. According to compressive sensing theory, the l1-norm minimization could yield the same sparse solution as the l0 norm under certain conditions. However, the computational complexity of the l1-norm optimization process is often too high for large-scale high-dimensional data, such as hyperspectral imagery (HSI). To make matter worse, a large number of training data are required to cover the whole sample space, which is difficult to obtain for hyperspectral data in practice. Recent advances have revealed that it is the collaborative representation but not the l1-norm sparsity that makes the SRC scheme powerful. Therefore, in this paper, a 3-D Gabor feature-based collaborative representation (3GCR) approach is proposed for HSI classification. When 3-D Gabor transformation could significantly increase the discrimination power of material features, a nonparametric and effective l2-norm collaborative representation method is developed to calculate the coefficients. Due to the simplicity of the method, the computational cost has been substantially reduced; thus, all the extracted Gabor features can be directly utilized to code the test sample, which conversely makes the l2-norm collaborative representation robust to noise and greatly improves the classification accuracy. The extensive experiments on two real hyperspectral data sets have shown higher performance of the proposed 3GCR over the state-of-the-art methods in the literature, in terms of both the classifier complexity and generalization ability from very small training sets. Numéro de notice : A2015-106 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2334608 En ligne : 10.1109/TGRS.2014.2334608 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75624 [article]

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Geometric structure simplification of 3D building models / Qingquan Li in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)

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