Books on the topic 'Robot vision Mathematical models'

Ji suan zhi neng ji qi zai san wei biao mian sao miao ji qi ren xi tong zhong de ying yong. Dalian Shi: Dalian hai shi da xue chu ban she, 2012.

Bochsler, Daniel C. Robotic space simulation: Integration of vision algorithms into an orbital operations simulation. [Houston, Tex.]: Research Institute for Computing and Information Systems, University of Houston--Clear Lake, 1987.

Jaklič, Aleš. Segmentation and recovery of superquadrics. Dordrecht: Kluwer Academic Publishers, 2000.

International Workshop on Visuomotor Coordination in Amphibians: Experiments, Comparisons, Models, and Robots (1987 Kassel, Germany). Visuomotor coordination: Amphibians, comparisons, models, and robots. New York: Plenum Press, 1989.

Paragios, Nikos, Yunmei Chen, and Olivier Faugeras, eds. Handbook of Mathematical Models in Computer Vision. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-28831-7.

Megahed, Saïd M. Principles of robot modelling and simulation. Chichester: Wiley, 1993.

Megahed, Saïd M. Principles of robot modelling and simulation. Chichester: J. Wiley, 1993.

Stefan, Türk, ed. The DFVLR models 1 and 2 of the Manutec r3 robot. Oberpfaffenhofen: DFVLR, Institut für Dynamik der Flugsysteme, 1988.

Jepson, Allan D. Mixture models for optical flow computation. Toronto: University of Toronto, Dept. of Computer Science, 1993.

Jepson, Allan D. What is a percept? Toronto: University of Toronto, Dept. of Computer Science, 1993.

Cheung, Catherine Kwok-Wai. Eigenpaxels in low-level vision: A theory of cell development, function and organisation. [Downsview, Ont.]: University of Toronto, Institute for Aerospace Studies, 2002.

Symposium on Noise and Disorder in Vision (1987 Toronto, Ont.). Symposium on Noise and Disorder in Vision: 1987 lectures in vision, University of Toronto. Toronto: University of Toronto, Dept. of Computer Science, 1987.

Chen, Ke, Carola-Bibiane Schönlieb, Xue-Cheng Tai, and Laurent Younces, eds. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-03009-4.

Li, S. Z. Markov random field modeling in computer vision. New York: Springer-Verlag, 1995.

Xiao, Bai, Jian Cheng, and Edwin R. Hancock. Graph-based methods in computer vision: Developments and applications. Hershey: Information Science Reference, 2012.

Barker, L. Keith. Theoretical three- and four-axis gimbal robot wrists. [s.l.]: National Aeronautics and Space Administration Scientific and Technical Information Branch, 1986.

Amini, Amir A. Measurement of Cardiac Deformations from MRI: Physical and Mathematical Models. Dordrecht: Springer Netherlands, 2002.

B, Fisher R., and Institute of Mathemtics and Its Applications., eds. Design and application of curves and surfaces: Mathematics of surfaces V : based on the proceedings of the fifth Conference on the Mathematics of Surfaces organized by the Institute of Mathematics and its Applications, held in Edinburgh in September 1992. Oxford: Clarendon Press, 1994.

1931-, Rosenfeld Azriel, ed. A pyramid framework for early vision: Multiresolutional computer vision. Dordrecht: Kluwer Academic Publishers, 1994.

Petitot, Jean. Neurogéométrie de la vision: Modèles mathématiques et physiques des architectures fonctionnelles. [Palaiseau]: Les Éditions de l'École Polytechnique, 2008.

K, Hung George, and Ciuffreda Kenneth J. 1947-, eds. Models of the visual system. New York: Kluwer Academic/Plenum Publishers, 2002.

N, Wilson Joseph, ed. Handbook of computer vision algorithms in image algebra. 2nd ed. Boca Raton: CRC Press, 2001.

N, Wilson Joseph, ed. Handbook of computer vision algorithms in image algebra. Boca Raton: CRC Press, 1996.

G, Gettinby, ed. Experimental design techniques in statistical practice: A practical software-based approach. Chichester, W. Sussex, England: Horwood Pub., 1998.

Ming-Chih, Chien, ed. Adaptive control of robot manipulators: A unified regressor-free approach. New Jersey: World Scientific Publishing, 2010.

Physics-based deformable models: Applications to computer vision, graphics, and medical imaging. Boston: Kluwer Academic, 1997.

Symposium of Mathematical Aspects of Image Processing and Computer Vision (10th 2010 Sapporo-shi, Japan). Mathematical aspects of image processing and computer vision 2010: Research Center for Integrative Mathematics symposium : the 10th symposium of MAIPCV. Sapporo: Research Center for Integrative Mathematics, Hokkaido University, 2010.

CIE Technical Committee TC-8-01. A colour appearance model for colour management systems: CIEAMO2. Vienna, Austria: CIE Central Bureau, 2004.

Postaire, Jack-Gérard. De l'image à la décision: Analyse des images numériques et théorie de la décision. [Paris]: Dunod, 1987.

Informat Łsionnai Ła teorii Ła identifikat Łsii. Moskva: Nauka, Fizmatlit, 1995.

Han, Ding, and Xiong You-Lun, eds. Fundamentals of robotic grasping and fixturing. Singapore: World Scientific, 2007.

Marr, David. Vision: A computational investigation into the human representation and processing of visual information. Cambridge, Mass: MIT Press, 2010.

Vision: A computational investigation into the human representation and processing of visual information. Cambridge, MA: MIT Press, 2010.

A computational perspective on visual attention. Cambridge, Mass: MIT Press, 2011.

Xing, Jing. Reexamination of color vision standards. Washington, D.C: Federal Aviation Administration, Office of Aerospace Medicine, 2006.

Perus, Mitja. Biological and quantum computing for human vision: Holonomic models and applications. Hershey, PA: Medical Information Science Reference, 2011.

Metaxas, Dimitris N. Physics-Based Deformable Models: Applications to Computer Vision, Graphics and Medical Imaging. Boston, MA: Springer US, 1997.

Barron, John Leonard. Computing motion and structure from noisy, time-varying image velocity information. Toronto: University of Toronto, Dept. of Computer Science, 1988.

Hyvärinen, Aapo. Natural Image Statistics: A Probabilistic Approach to Early Computational Vision. London: Springer London, 2009.

Szeliski, Richard. Bayesian modeling of uncertainty in low-level vision. Boston: Kluwer Academic Publishers, 1989.

Kiong, Loo Chu. Biological and quantum computing for human vision: Holonomic models and applications. Hershey, PA: Medical Information Science Reference, 2011.

Zhao, Jingshan. Ji qi ren ji gou zi you du fen xi li lun =: Analytical theory of degrees of freedom for robot mechanisms. Bei jing: Ke xue chu ban she, 2009.

Bart M. ter Haar Romeny. Front-end vision and multi-scale image analysis: Multi-scale computer vision theory and applications, written in Mathematica. Dordrecht: Kluwer Academic, 2003.

Romeny, Bart M. ter Haar. Front-end vision and multi-scale image analysis: Multi-scale computer vision theory and applications, written in Mathematica. [Dordrecht]: Springer, 2008.

Bart M. ter Haar Romeny. Front-end vision and multi-scale image analysis: Multi-scale computer vision theory and applications, written in Mathematica. [Dordrecht]: Springer, 2008.

1959-, Valentine Tim, British Psychological Society. Welsh Branch., and International Conference on Face Processing (1993 : Cardiff, Wales), eds. Cognitive and computational aspects of face recognition: Explorations in face space. London: Routledge, 1995.

1965-, Zhang Zhengyou, ed. Boosting-based face detection and adaptation. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2010.

Ali, Mohamad-Djafari, ed. Inverse problems in vision and 3D tomography. London: ISTE, 2009.

Choudhary, Alok N. NETRA, a parallel architecture for integrated vision systems. [Urbana, Ill.]: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1989.

Choudhary, Alok N. NETRA, a parallel architecture for integrated vision systems. [Urbana, Ill.]: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1989.