Relevant bibliographies by topics / Reconstruction 3D de la scene

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Reconstruction 3D de la scene'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "Reconstruction 3D de la scene"

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Wen, Mingyun, and Kyungeun Cho. "Object-Aware 3D Scene Reconstruction from Single 2D Images of Indoor Scenes." Mathematics 11, no. 2 (2023): 403. http://dx.doi.org/10.3390/math11020403.

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Recent studies have shown that deep learning achieves excellent performance in reconstructing 3D scenes from multiview images or videos. However, these reconstructions do not provide the identities of objects, and object identification is necessary for a scene to be functional in virtual reality or interactive applications. The objects in a scene reconstructed as one mesh are treated as a single object, rather than individual entities that can be interacted with or manipulated. Reconstructing an object-aware 3D scene from a single 2D image is challenging because the image conversion process fr
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Guo, Rui Bin, Tao Guan, Dong Xiang Zhou, Ke Ju Peng, and Wei Hong Fan. "Efficient Multi-Scale Registration of 3D Reconstructions Based on Camera Center Constraint." Advanced Materials Research 998-999 (July 2014): 1018–23. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.1018.

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Recent approaches for reconstructing 3D scenes from image collections only produce single scene models. To build a unified scene model that contains multiple subsets, we present a novel method for registration of 3D scene reconstructions in different scales. It first normalizes the scales of the models building on similarity reconstruction by the constraint of the 3D position of shared cameras. Then we use Cayley transform to fit the matrix of coordinates transformation for the models in normalization scales. The experimental results show the effectiveness and scalability of the proposed appro
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Jang, Hyeonjoong, Andréas Meuleman, Dahyun Kang, Donggun Kim, Christian Richardt, and Min H. Kim. "Egocentric scene reconstruction from an omnidirectional video." ACM Transactions on Graphics 41, no. 4 (2022): 1–12. http://dx.doi.org/10.1145/3528223.3530074.

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Omnidirectional videos capture environmental scenes effectively, but they have rarely been used for geometry reconstruction. In this work, we propose an egocentric 3D reconstruction method that can acquire scene geometry with high accuracy from a short egocentric omnidirectional video. To this end, we first estimate per-frame depth using a spherical disparity network. We then fuse per-frame depth estimates into a novel spherical binoctree data structure that is specifically designed to tolerate spherical depth estimation errors. By subdividing the spherical space into binary tree and octree no
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Buck, Ursula. "3D crime scene reconstruction." Forensic Science International 304 (November 2019): 109901. http://dx.doi.org/10.1016/j.forsciint.2019.109901.

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Gao, Huanbing, Lei Liu, Ya Tian, and Shouyin Lu. "3D Reconstruction for Road Scene with Obstacle Detection Feedback." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 12 (2018): 1855021. http://dx.doi.org/10.1142/s0218001418550212.

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This paper presented 3D reconstruction method for road scene with the help of obstacle detection. 3D reconstruction for road scene can be used in autonomous driving, driver assistance system, car navigation systems. However, some errors often rose when 3D reconstructing due to the shade from the moving object in the road scene. The presented 3D reconstruction method with obstacle detection feedback can avoid this problem. Firstly, this paper offers a framework for the 3D reconstruction of road scene by laser scanning and vision. A calibration method based on the location of horizon is proposed
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Liu, Yilin, Liqiang Lin, Yue Hu, et al. "Learning Reconstructability for Drone Aerial Path Planning." ACM Transactions on Graphics 41, no. 6 (2022): 1–17. http://dx.doi.org/10.1145/3550454.3555433.

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We introduce the first learning-based reconstructability predictor to improve view and path planning for large-scale 3D urban scene acquisition using unmanned drones. In contrast to previous heuristic approaches, our method learns a model that explicitly predicts how well a 3D urban scene will be reconstructed from a set of viewpoints. To make such a model trainable and simultaneously applicable to drone path planning, we simulate the proxy-based 3D scene reconstruction during training to set up the prediction. Specifically, the neural network we design is trained to predict the scene reconstr
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Dong, Bo, Kaiqiang Chen, Zhirui Wang, Menglong Yan, Jiaojiao Gu, and Xian Sun. "MM-NeRF: Large-Scale Scene Representation with Multi-Resolution Hash Grid and Multi-View Priors Features." Electronics 13, no. 5 (2024): 844. http://dx.doi.org/10.3390/electronics13050844.

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Reconstructing large-scale scenes using Neural Radiance Fields (NeRFs) is a research hotspot in 3D computer vision. Existing MLP (multi-layer perception)-based methods often suffer from issues of underfitting and a lack of fine details in rendering large-scale scenes. Popular solutions are to divide the scene into small areas for separate modeling or to increase the layer scale of the MLP network. However, the subsequent problem is that the training cost increases. Moreover, reconstructing large scenes, unlike object-scale reconstruction, involves a geometrically considerable increase in the q
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Tingdahl, David, and Gool Van Luc. "An Enhanced On-Line Service for 3D Model Construction from Photographs." International Journal of Heritage in the Digital Era 1, no. 2 (2012): 277–94. http://dx.doi.org/10.1260/2047-4970.1.2.277.

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We present a web service for image based 3D reconstruction. The system allows a cultural heritage professional to easily create a 3D model of a scene or object out of images taken from different viewpoints. The user uploads the images to our server on which all processing takes place, and the final result can be downloaded upon completion. Any consumer-class digital camera can be used, and the system is free to use for non-commercial purposes. The service includes a number of innovations to greatly simplify the process of taking pictures suitable for reconstruction. In particular, we are able
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Wang, Wei, Fengjiao Gao, and Yongliang Shen. "Res-NeuS: Deep Residuals and Neural Implicit Surface Learning for Multi-View Reconstruction." Sensors 24, no. 3 (2024): 881. http://dx.doi.org/10.3390/s24030881.

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Surface reconstruction using neural networks has proven effective in reconstructing dense 3D surfaces through image-based neural rendering. Nevertheless, current methods are challenging when dealing with the intricate details of large-scale scenes. The high-fidelity reconstruction performance of neural rendering is constrained by the view sparsity and structural complexity of such scenes. In this paper, we present Res-NeuS, a method combining ResNet-50 and neural surface rendering for dense 3D reconstruction. Specifically, we present appearance embeddings: ResNet-50 is used to extract the appe
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Xia, Wei, Rongfeng Lu, Yaoqi Sun, et al. "3D Indoor Scene Completion via Room Layout Estimation." Journal of Physics: Conference Series 2025, no. 1 (2021): 012102. http://dx.doi.org/10.1088/1742-6596/2025/1/012102.

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Abstract Recent advances in 3D reconstructions have shown impressive progress in 3D indoor scene reconstruction, enabling automatic scene modeling; however, holes in the 3D scans hinder the further usage of the reconstructed models. Thus, we propose the task of layout-based hole filling for the incomplete indoor scene scans: from the mesh of a scene model, we estimate the scene layout by detecting the principal planes of a scene and leverage the layout as the prior for the accurate completion of planar regions. Experiments show that guiding scene model completion through the scene layout prior
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Dissertations / Theses on the topic "Reconstruction 3D de la scene"

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Boyling, Timothy A. "Active vision for autonomous 3D scene reconstruction." Thesis, University of Glasgow, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433622.

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Nitschke, Christian. "3D reconstruction : real-time volumetric scene reconstruction from multiple views /." Saarbrücken : VDM Verl. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2939698&prov=M&dok_var=1&dok_ext=htm.

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Roldão, Jimenez Luis Guillermo. "3D Scene Reconstruction and Completion for Autonomous Driving." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS415.

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Dans cette thèse, nous nous intéressons à des problèmes liés à la reconstruction et la complétion des scènes 3D à partir de nuages de points de densité hétérogène. Nous étudions l'utilisation de grilles d'occupation tridimensionnelles pour la reconstruction d'une scène 3D à partir de plusieurs observations. Nous proposons d'exploiter les informations de trajet des rayons pour résoudre des ambiguïtés dans les cellules partiellement occupées. Notre approche permet de réduire les imprécisions dues à la discrétisation et d'effectuer des mises à jour d'occupation des cellules dans des scénarios dyn
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Goldman, Benjamin Joseph. "Broadband World Modeling and Scene Reconstruction." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23094.

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Perception is a key feature in how any creature or autonomous system relates to its environment. While there are many types of perception, this thesis focuses on the improvement of the visual robotics perception systems. By implementing a broadband passive sensing system in conjunction with current perception algorithms, this thesis explores scene reconstruction and world modeling. <br />The process involves two main steps. The first is stereo correspondence using block matching algorithms with filtering to improve the quality of this matching process. The disparity maps are then transformed i
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Booth, Roy. "Scene analysis and 3D object reconstruction using passive vision." Thesis, University of Newcastle Upon Tyne, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295780.

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Aufderheide, Dominik. "VISrec! : visual-inertial sensor fusion for 3D scene reconstruction." Thesis, University of Bolton, 2014. http://ubir.bolton.ac.uk/649/.

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The self-acting generation of three-dimensional models, by analysing monocular image streams from standard cameras, is one fundamental problem in the field of computer vision. A prerequisite for the scene modelling is the computation of the camera pose for the different frames of the sequence. Several techniques and methodologies have been introduced during the last decade to solve this classical Structure from Motion (SfM) problem, which incorporates camera egomotion estimation and subsequent recovery of 3D scene structure. However the applicability of those approaches to real world devices a
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Chandraker, Manmohan Krishna. "From pictures to 3D global optimization for scene reconstruction /." Diss., [La Jolla] : University of California, San Diego, 2009. http://wwwlib.umi.com/cr/ucsd/fullcit?p3369041.

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Thesis (Ph. D.)--University of California, San Diego, 2009.<br>Title from first page of PDF file (viewed September 15, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 235-246).
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Manessis, A. "3D reconstruction from video using a mobile robot." Thesis, University of Surrey, 2001. http://epubs.surrey.ac.uk/844129/.

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An autonomous robot able to navigate inside an unknown environment and reconstruct full 3D scene models using monocular video has been a long term goal in the field of Machine Vision. A key component of such a system is the reconstruction of surface models from estimated scene structure. Sparse 3D measurements of real scenes are readily estimated from N-view image sequences using structure-from-motion techniques. In this thesis we present a geometric theory for reconstruction of surface models from sparse 3D data captured from N camera views. Based on this theory we introduce a general N-view
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Moodie, Daniel Thien-An. "Sensor Fused Scene Reconstruction and Surface Inspection." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/47453.

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Optical three dimensional (3D) mapping routines are used in inspection robots to detect faults by creating 3D reconstructions of environments. To detect surface faults, sub millimeter depth resolution is required to determine minute differences caused by coating loss and pitting. Sensors that can detect these small depth differences cannot quickly create contextual maps of large environments. To solve the 3D mapping problem, a sensor fused approach is proposed that can gather contextual information about large environments with one depth sensor and a SLAM routine; while local surface defects
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D'Angelo, Paolo. "3D scene reconstruction by integration of photometric and geometric methods." [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=985352949.

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Books on the topic "Reconstruction 3D de la scene"

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Nitschke, Christian. 3D reconstruction: Real-time volumetric scene reconstruction from multiple views. VDM, Verlag Dr. Müller, 2007.

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Weinmann, Martin. Reconstruction and Analysis of 3D Scenes. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29246-5.

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Bellocchio, Francesco, N. Alberto Borghese, Stefano Ferrari, and Vincenzo Piuri. 3D Surface Reconstruction. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5632-2.

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Zhang, Zhengyou, and Olivier Faugeras. 3D Dynamic Scene Analysis. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-58148-9.

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1948-, DeHaan John D., ed. Forensic fire scene reconstruction. Prentice-Hall, 2004.

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1948-, DeHaan John D., ed. Forensic fire scene reconstruction. 2nd ed. Pearson/Prentice Hall, 2009.

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Icove, David J. Forensic fire scene reconstruction. 2nd ed. Pearson/Prentice Hall, 2009.

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Abdelguerfi, Mahdi, ed. 3D Synthetic Environment Reconstruction. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4419-8756-3.

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International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, (2nd : 1993 : Snowbird, Utah), ed. Fully 3D image reconstruction. IOP Publishing, 1994.

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Mahdi, Abdelguerfi, ed. 3D synthetic environment reconstruction. Kluwer Academic Publishers, 2001.

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Book chapters on the topic "Reconstruction 3D de la scene"

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Lucas, Laurent, Céline Loscos, and Yannick Remion. "3D Scene Reconstruction and Structuring." In 3D Video. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118761915.ch8.

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Weinmann, Martin. "3D Scene Analysis." In Reconstruction and Analysis of 3D Scenes. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29246-5_6.

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Chen, Jian, Bingxi Jia, and Kaixiang Zhang. "Road Scene 3D Reconstruction." In Multi-View Geometry Based Visual Perception and Control of Robotic Systems. CRC Press, 2018. http://dx.doi.org/10.1201/9780429489211-5.

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Zhang, Zhengyou, and Olivier Faugeras. "Reconstruction of 3D Line Segments." In 3D Dynamic Scene Analysis. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-58148-9_3.

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Morana, Marco. "3D Scene Reconstruction Using Kinect." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03992-3_13.

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Hartley, Richard, and Gilles Debunne. "Dualizing Scene Reconstruction Algorithms." In 3D Structure from Multiple Images of Large-Scale Environments. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49437-5_2.

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Jiang, Cansen, Yohan Fougerolle, David Fofi, and Cédric Demonceaux. "Dynamic 3D Scene Reconstruction and Enhancement." In Image Analysis and Processing - ICIAP 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68560-1_46.

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Lucas, Laurent, Céline Loscos, and Yannick Remion. "3D Reconstruction of Sport Scenes." In 3D Video. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118761915.ch21.

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Miller, Corey A., and Thomas J. Walls. "Passive 3D Scene Reconstruction via Hyperspectral Imagery." In Advances in Visual Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14249-4_39.

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Denninger, Maximilian, and Rudolph Triebel. "3D Scene Reconstruction from a Single Viewport." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58542-6_4.

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Conference papers on the topic "Reconstruction 3D de la scene"

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Little, Charles Q., Daniel E. Small, Ralph R. Peters, and J. B. Rigdon. "Forensic 3D scene reconstruction." In 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, edited by William R. Oliver. SPIE, 2000. http://dx.doi.org/10.1117/12.384885.

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Liu, Juan, Shijie Zhang, and Haowen Ma. "Real-time Holographic Display based on Dynamic Scene Reconstruction and Rendering." In 3D Image Acquisition and Display: Technology, Perception and Applications. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/3d.2023.dw5a.1.

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We propose an end-to-end real-time holographic display based on real-time capture of real scenes with simple system composition and affordable hardware requirements, the proposed technique will break the dilemma of the existing real-scene holographic display.
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Shen, Yangping, Yoshitsugu Manabe, and Noriko Yata. "3D scene reconstruction and object recognition for indoor scene." In International Workshop on Advanced Image Technology, edited by Phooi Yee Lau, Kazuya Hayase, Qian Kemao, et al. SPIE, 2019. http://dx.doi.org/10.1117/12.2521492.

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Sabharwal, Chaman L. "Stereoscopic projections and 3D scene reconstruction." In the 1992 ACM/SIGAPP symposium. ACM Press, 1992. http://dx.doi.org/10.1145/130069.130155.

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Shan, Qi, Riley Adams, Brian Curless, Yasutaka Furukawa, and Steven M. Seitz. "The Visual Turing Test for Scene Reconstruction." In 2013 International Conference on 3D Vision (3DV). IEEE, 2013. http://dx.doi.org/10.1109/3dv.2013.12.

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Da Silveira, Thiago L. T., and Cláudio R. Jung. "Dense 3D Indoor Scene Reconstruction from Spherical Images." In Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/sibgrapi.est.2020.12977.

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Techniques for 3D reconstruction of scenes based on images are popular and support a number of secondary applications. Traditional approaches require several captures for covering whole environments due to the narrow field of view (FoV) of the pinhole-based/perspective cameras. This paper summarizes the main contributions of the homonym Ph.D. Thesis, which addresses the 3D scene reconstruction problem by considering omnidirectional (spherical or 360◦ ) cameras that present a 360◦ × 180◦ FoV. Although spherical imagery have the benefit of the full-FoV, they are also challenging due to the inher
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Huzaifa, Muhammad, Boyuan Tian, Yihan Pang, Henry Che, Shenlong Wang, and Sarita Adve. "ADAPTIVEFUSION: Low Power Scene Reconstruction." In 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 2023. http://dx.doi.org/10.1109/vrw58643.2023.00296.

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Miksik, Ondrej, Yousef Amar, Vibhav Vineet, Patrick Perez, and Philip H. S. Torr. "Incremental dense multi-modal 3D scene reconstruction." In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2015. http://dx.doi.org/10.1109/iros.2015.7353479.

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Hane, Christian, Christopher Zach, Andrea Cohen, Roland Angst, and Marc Pollefeys. "Joint 3D Scene Reconstruction and Class Segmentation." In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.20.

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McBride, Jonah C., Magnus S. Snorrason, Thomas R. Goodsell, Ross S. Eaton, and Mark R. Stevens. "3D scene reconstruction: why, when, and how?" In Defense and Security, edited by Grant R. Gerhart, Chuck M. Shoemaker, and Douglas W. Gage. SPIE, 2004. http://dx.doi.org/10.1117/12.542678.

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Reports on the topic "Reconstruction 3D de la scene"

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Defrise, Michel, and Grant T. Gullberg. 3D reconstruction of tensors and vectors. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/838184.

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Lyckegaard, A., A. Alpers, W. Ludwig, et al. 3D Grain Reconstruction from Boxscan Data. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada530190.

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Weiss, Isaac. 3D Curve Reconstruction From Uncalibrated Cameras. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada306610.

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Rother, Diego, Kedar Patwardhan, Iman Aganj, and Guillermo Sapiro. 3D Priors for Scene Learning from a Single View. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada513268.

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KRUHL, Jörn H., Robert MARSCHALLINGER, Kai-Uwe HESS, Asher FLAWS, and Richard ZEFACK KHEMAKA. 3D fabric recording by neutron tomography: benchmarking with destructive 3D reconstruction. Cogeo@oeaw-giscience, 2010. http://dx.doi.org/10.5242/cogeo.2010.0009.

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KRUHL, Jörn H., Robert MARSCHALLINGER, Kai-Uwe HESS, Asher FLAWS, and Richard ZEFACK KHEMAKA. 3D fabric recording by neutron tomography: benchmarking with destructive 3D reconstruction. Cogeo@oeaw-giscience, 2010. http://dx.doi.org/10.5242/cogeo.2010.0009.a01.

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Rosales, Romer, Vassilis Athitsos, Leonid Sigal, and Stan Sclaroff. 3D Hand Pose Reconstruction Using Specialized Mappings. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada451286.

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Blankenbecler, Richard. 3D Image Reconstruction: Determination of Pattern Orientation. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/812988.

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Scott, Logan, and Thomas Karnowski. An Evaluation of Three Dimensional Scene Reconstruction Tools for Safeguards Applications. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2205425.

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Tyler, Christopher W., and Tai-Sing Lee. Encoding of 3D Structure in the Visual Scene: A New Conceptualization. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada580528.

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