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Histograms of oriented mosaic gradients for snapshot spectral image description / Lulu Chen in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 183 (January 2022) . - pp 79 - 93 Titre : Histograms of oriented mosaic gradients for snapshot spectral image description Type de document : Article/Communication Auteurs : Lulu Chen, Auteur ; Yong-Qiang Zhao, Auteur ; Jonathan Cheung-Wai Chan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 79 - 93 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] capteur multibande [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] extraction de traits caractéristiques [Termes IGN] filtre spectral [Termes IGN] histogramme [Termes IGN] image proche infrarouge [Termes IGN] image spectrale [Termes IGN] mosaïque d'images [Termes IGN] poursuite de cible [Termes IGN] temps instantané Résumé : (auteur) This paper presents a feature descriptor using Histogram of Oriented Mosaic Gradient (HOMG) that extracts spatial-spectral features directly from mosaic spectral images. Spectral imaging utilizes unique spectral signatures to distinguish objects of interest in the scene more discriminatively. Snapshot spectral cameras equipped with spectral filter arrays (SFAs) capture spectral videos in real time, making it possible to detect/track fast moving targets based on spectral imaging. How to effectively extract the spatial-spectral feature directly from the mosaic spectral images acquired by snapshot spectral cameras is a core issue for detection/tracking. So far, there is a lack of comprehensive and in-depth research on this issue. To this end, this paper proposed a new spatial-spectral feature extractor for mosaic spectral images. The proposed scheme finds two forms of SFA neighborhood (SFAN) to construct a feature extractor suitable for any SFA structure. Exploiting the spatial-spectral correlation in two SFANs, we design six mosaic spatial-spectral gradient operators to compute spatial-spectral gradient maps (SGMs). HOMG descriptors are constructed using the magnitude and orientation of SGMs. The effectiveness and generalizability of the proposed method have been verified with object tracking experiments. Compared to the state-of-the-art feature descriptors, HOMG ranked first on two datasets captured with snapshot spectral camera with different SFAs, achieving a gain of 3.9% and 5.9% in average success rate over the second-ranked feature. Numéro de notice : A2022-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.10.018 Date de publication en ligne : 12/11/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.10.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99058 [article]

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Multiple convolutional features in Siamese networks for object tracking / Zhenxi Li in Machine Vision and Applications, vol 32 n° 3 (May 2021)  

Public [article]  inMachine Vision and Applications > vol 32 n° 3 (May 2021) . - n° 59 Titre : Multiple convolutional features in Siamese networks for object tracking Type de document : Article/Communication Auteurs : Zhenxi Li, Auteur ; Guillaume-Alexandre Bilodeau, Auteur ; Wassim Bouachir, Auteur Année de publication : 2021 Article en page(s) : n° 59 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] approche hiérarchique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] extraction de traits caractéristiques [Termes IGN] poursuite de cible [Termes IGN] reconnaissance d'objets [Termes IGN] réseau neuronal siamois Résumé : (auteur) Siamese trackers demonstrated high performance in object tracking due to their balance between accuracy and speed. Unlike classification-based CNNs, deep similarity networks are specifically designed to address the image similarity problem and thus are inherently more appropriate for the tracking task. However, Siamese trackers mainly use the last convolutional layers for similarity analysis and target search, which restricts their performance. In this paper, we argue that using a single convolutional layer as feature representation is not an optimal choice in a deep similarity framework. We present a Multiple Features-Siamese Tracker (MFST), a novel tracking algorithm exploiting several hierarchical feature maps for robust tracking. Since convolutional layers provide several abstraction levels in characterizing an object, fusing hierarchical features allows to obtain a richer and more efficient representation of the target. Moreover, we handle the target appearance variations by calibrating the deep features extracted from two different CNN models. Based on this advanced feature representation, our method achieves high tracking accuracy, while outperforming the standard siamese tracker on object tracking benchmarks. The source code and trained models are available at https://github.com/zhenxili96/MFST. Numéro de notice : A2021-470 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00138-021-01185-7 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.1007/s00138-021-01185-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97903 [article]

A scanning LiDAR for long range detection and tracking of UAVs / Alain Quentel (2021)  

Public Titre : A scanning LiDAR for long range detection and tracking of UAVs Type de document : Thèse/HDR Auteurs : Alain Quentel, Auteur ; Yohan Dupuis, Directeur de thèse Editeur : Rouen : Université de Rouen Année de publication : 2021 Importance : 159 p. Format : 21 x 30 cm Note générale : bibliographie Thèse pour obtenir le diplôme de Doctorat, spécialité Electronique, microélectronique, optique et lasers, optoélectronique microondes robotique Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] drone [Termes IGN] optimisation (mathématiques) [Termes IGN] poursuite de cible [Termes IGN] réflectivité [Termes IGN] télémètre laser aéroporté [Termes IGN] télémétrie laser aéroporté [Termes IGN] temps de vol Index. décimale : THESE Thèses et HDR Résumé : (auteur) Misuse of civil drones, or UAVs (unmanned aerial vehicles) has been a rising concern in the past few years. As a response, multiple systems including optics, electronics and even acoustics technologies have been developed for detection and tracking. Unfortunately, UAVs represent a challenging target to detect and track due to their small, decimetric size and large variability of shapes and behaviors. In this PhD, we developed and optimized a LiDAR (light detection and ranging) system to tackle this issue to distances up to a kilometer. In our system, range is acquired using the time of flight principle, and imagery done by sequentially scanning the scene with a dual-axis galvanometer. We took advantage of the scanning versatility to develop several operating modes. A standard detection mode captures the image of the scene using a raster-scan of large field of view. Tracking mode is based on a local pattern surrounding the target, which is updated at a very high rate to keep the target within its boundaries. Efforts were put into a theoretical and numerical optimization study of the numerous parameters involved in our scanning LiDAR, so as to reach sufficient performances in term of maximal range, localization resolution and rate. Pattern optimization for both detection and tracking mode was a primary focus, using the target probability of detection as the function to maximize. Target size, speed and reflectivity was also introduced in the probability of detection, giving a complete overview of the system performance. On our LiDAR platform, developed from the ground up, each component was characterized to enrich and validate our models. This prototype was tested for UAVs detection and tracking during several weeks of trials. Following this success, a pre-industrial integration process was launched and supervised by the candidate. Numéro de notice : 28535 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de doctorat : Electronique, microélectronique, optique et lasers, optoélectronique microondes robotique : Rouen : 2021 Organisme de stage : Institut de Recherche en Systèmes Electroniques Embarqués DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-03228683 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99312

Integrated Kalman filter of accurate ranging and tracking with wideband radar / Shaopeng Wei in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 58 n° 12 (December 2020) . - pp 8395 - 8411 Titre : Integrated Kalman filter of accurate ranging and tracking with wideband radar Type de document : Article/Communication Auteurs : Shaopeng Wei, Auteur ; Lei Zhang, Auteur ; Hongwei Liu, Auteur Année de publication : 2020 Article en page(s) : pp 8395 - 8411 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande spectrale [Termes IGN] filtrage bayésien [Termes IGN] filtre de Kalman [Termes IGN] inférence statistique [Termes IGN] largeur de bande [Termes IGN] phase [Termes IGN] poursuite de cible [Termes IGN] seuillage d'image [Termes IGN] signal Résumé : (auteur) Accurate ranging and wideband tracking are treated as two independent and separate processes in traditional radar systems. As a result, limited by low data rate due to nonsequential processing, accurate ranging usually performs low efficiency in practical application. Similarly, without applying accurate ranging, the data after thresholding and clustering are used in wideband tracking, leading to a significant decrease in tracking accuracy. In this article, an integrated Kalman filter of accurate ranging and tracking is proposed using methods of phase-derived-ranging and Bayesian inference in wideband radar. Besides the motion state, in this integrated Kalman filter, the complex-valued high-resolution range profile (HRRP) is also introduced as a reference signal by coherent integration in a sliding window, which incorporates target’s scattering distribution and phase characteristics. Corresponding kinetic equations are derived to predict the motion state and the reference signal in the next moment. A ranging process is constructed based on the received signal and the predicted reference signal in order to estimate innovation using methods of phase-derived-ranging and Bayesian inference, and a sequential update for motion state can be accomplished with the Kalman filter as well. In every recursion, the complex-valued reference signal is also updated by coherently integrating the latest pulses. The integrated Kalman filter takes full use of high range resolution and phase information, improving both efficiency and precision compared with conventional approaches of ranging and wideband tracking. Implemented in a sequential manner, the integrated Kalman filter can be applied in a real-time application, realizing simultaneous ranging with high precision and wideband tracking. Finally, simulated and real-measured experiments confirm the remarkable performance. Numéro de notice : A2020-740 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2987854 Date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2987854 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96367 [article]

Sensor tasking for search and catalog maintenance of geosynchronous space objects / Han Cai in Acta Astronautica, vol 175 (October 2020)  

Public [article]  inActa Astronautica > vol 175 (October 2020) . - pp 234 - 248 Titre : Sensor tasking for search and catalog maintenance of geosynchronous space objects Type de document : Article/Communication Auteurs : Han Cai, Auteur ; Yang Yang, Auteur ; Steve Gehly, Auteur ; Changyong He , Auteur ; Moriba Jah, Auteur Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : pp 234 - 248 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales [Termes IGN] catalogue [Termes IGN] débris spatial [Termes IGN] méthode des éléments finis [Termes IGN] optimisation (mathématiques) [Termes IGN] orbite géostationnaire [Termes IGN] poursuite de cible [Termes IGN] théorie de Dempster-Shafer Résumé : (auteur) The space object catalog provides orbital state and characteristic information of space objects for critical applications in space situational awareness. Maintaining accurate states for all objects in the catalog is essential, but it leads to large loads on sensors and limits the time available to search for new objects. This study proposes a novel sensor tasking method for search and catalog maintenance of space objects in Geosynchronous Earth Orbit (GEO). This new framework formulates sensor tasking as a multi-objective optimization problem. It seeks an optimal balance between sensor resources to search for new objects and to maintain precise state estimates for all objects in the catalog. In order to maintain custody of newly detected targets, an evidence-based decision-making method is used to effectively prompt follow-on tracking. The labeled multi-Bernoulli filter is employed to track existing and new space objects and provide refined orbital state estimation. Simulation results are presented, in which 100 cataloged GEO objects and 200 new GEO objects are tracked using a space-based sensor placed on a Sun-synchronous orbit. Numéro de notice : A2020-419 Affiliation des auteurs : ENSG+Ext (2012-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.actaastro.2020.05.063 Date de publication en ligne : 01/06/2020 En ligne : https://doi.org/10.1016/j.actaastro.2020.05.063 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95550 [article]

Visual object tracking with deep neural networks / Pier Luigi Mazzeo (2019)  

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Adaptive correlation filters with long-term and short-term memory for object tracking / Chao Ma in International journal of computer vision, vol 126 n° 8 (August 2018)  

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Object tracking with robotic total stations : current technologies and improvements based on image data / Matthias Ehrhart in Journal of applied geodesy, vol 11 n° 3 (September 2017)  

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Motion priors based on goals hierarchies in pedestrian tracking applications / Francisco Madrigal in Machine Vision and Applications, vol 28 n° 3-4 (May 2017)  

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Probabilistic multi-person localisation and tracking / Tobias Klinger (2016) 

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Tracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data / Siavash Hosseinyalamdary in ISPRS International journal of geo-information, vol 4 n°3 (September 2015)  

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Tracking-Learning-Detection / Zdenek Kalal in IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, vol 34 n° 7 (July 2012)

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Indoor pedestrian navigation using foot-mounted IMU and portable ultrasound range sensors / Gabriel Girard in Sensors, vol 11 n° 8 (August 2011)  

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Photogrammetric image analysis PIA 11, Munich, Germany, October 5-7, 2011 / Uwe Stilla (2011)  

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