Camera Calibration

Camera calibration toolbox for MATLAB. Computer Vision System Toolbox™ provides algorithms, functions, and apps for designing and simulating computer vision and video processing systems. You can perform feature detection, extraction, and matching; object detection and tracking; motion estimation; and video processing. For 3-D computer vision, the system toolbox supports camera calibration, stereo vision, 3-D reconstruction, and 3-D point cloud processing. With machine learning based frameworks, you can train object detection, object recognition, and image retrieval systems. Algorithms are available as MATLAB® functions, System objects, and Simulink® blocks. For rapid prototyping and embedded system design, the system toolbox supports fixed-point arithmetic and C-code generation.

References in zbMATH (referenced in 46 articles )

Showing results 1 to 20 of 46.
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  1. Gaspar, Tiago; Oliveira, Paulo; Favaro, Paolo: Synchronization of independently moving cameras via motion recovery (2016)
  2. Collins, Toby; Bartoli, Adrien: Infinitesimal plane-based pose estimation (2014)
  3. Liu, Feng; Zhang, David: 3D fingerprint reconstruction system using feature correspondences and prior estimated finger model (2014)
  4. Vera, Pablo; Zenteno, Daniel; Salas, Joaquín: A smartphone-based virtual white cane (2014)
  5. Chen, Zhihu; Wong, Kwan-Yee K.; Matsushita, Yasuyuki; Zhu, Xiaolong: Depth from refraction using a transparent medium with unknown pose and refractive index (2013)
  6. Carrillo, Luis Rodolfo García; López, Alejandro Enrique Dzul; Lozano, Rogelio; Pégard, Claude: Combining stereo vision and inertial navigation system for a quad-rotor UAV (2012)
  7. de França, José Alexandre; Stemmer, Marcelo Ricardo; de Morais França, Maria Bernadete; Piai, Juliani Chico: A new robust algorithmic for multi-camera calibration with a 1D object under general motions without prior knowledge of any camera intrinsic parameter (2012)
  8. Delbracio, Mauricio; Musé, Pablo; Almansa, Andrés; Morel, Jean-Michel: The non-parametric sub-pixel local point spread function estimation is a well posed problem (2012)
  9. Frosio, I.; Alzati, A.; Bertolini, M.; Turrini, C.; Borghese, N.A.: Linear pose estimate from corresponding conics (2012)
  10. Hofmann, M.; Gavrila, D.M.: Multi-view 3D human pose estimation in complex environment (2012)
  11. Prisacariu, Victor A.; Reid, Ian D.: PWP3D: real-time segmentation and tracking of 3D objects (2012)
  12. Zhao, Xu; Zhou, Zhong; Wu, Wei: Radiance-based color calibration for image-based modeling with multiple cameras (2012)
  13. Corke, Peter: Robotics, vision and control. Fundamental algorithms in MATLAB. (2011)
  14. Han, Kyung Min; Desouza, Guilherme N.: Geolocation of multiple targets from airborne video without terrain data (2011)
  15. Perriollat, Mathieu; Hartley, Richard; Bartoli, Adrien: Monocular template-based reconstruction of inextensible surfaces (2011)
  16. Roy, Arunesh; Gale, Nicholas; Hong, Lang: Automated traffic surveillance using fusion of Doppler radar and video information (2011)
  17. Shi, Fanhuai; Xi, Yongjian; Li, Xiaoling; Duan, Ye: An automation system of rooftop detection and 3D building modeling from aerial images (2011)
  18. Avni, Ofir; Baum, Tomer; Katzir, Gadi; Rivlin, Ehud: Recovery of 3D animal motions using cameras and mirrors (2010)
  19. Cappelle, Cindy; El Badaoui El Najjar, Maan; Pomorski, Denis; Charpillet, François: Intelligent geolocalization in urban areas using global positioning systems, three-dimensional geographic information systems, and vision (2010)
  20. Cleju, Ioan; Saupe, Dietmar: Evaluation of texture registration by epipolar geometry (2010)

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