Books on the topic 'Motion Estimation'

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1

Goh, Wooi Boon. Image motion estimation. [s.l.]: typescript, 1992.

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2

Chakrabarti, Indrajit, Kota Naga Srinivasarao Batta, and Sumit Kumar Chatterjee. Motion Estimation for Video Coding. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14376-7.

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3

Ong, Ee Ping. Robust motion estimation and segmentation. Birmingham: University of Birmingham, 1997.

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4

Furht, Borko, Joshua Greenberg, and Raymond Westwater. Motion Estimation Algorithms for Video Compression. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6241-2.

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5

Furht, Borivoje. Motion estimation algorithms for video compression. Boston: Kluwer Academic Publishers, 1997.

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6

Furht, Borko. Motion estimation algorithms for video compression. Boston, Mass: Kluwer, 1997.

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7

Furht, Borivoje. Motion Estimation Algorithms for Video Compression. Boston, MA: Springer US, 1997.

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8

Metkar, Shilpa, and Sanjay Talbar. Motion Estimation Techniques for Digital Video Coding. India: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1097-9.

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9

Ildiz, Faith. Estimation of motion parameters from image sequences. Monterey, Calif: Naval Postgraduate School, 1991.

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10

Metkar, Shilpa. Motion Estimation Techniques for Digital Video Coding. India: Springer India, 2013.

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11

Gibson, David Michael. Trajectory-based multi-frame motion estimation with applications to motion compensated prediction. Birmingham: University of Birmingham, 2001.

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12

Zwart, Christine M., and David H. Frakes. Control Grid Motion Estimation for Efficient Application of Optical Flow. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-01520-5.

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13

Ehrhardt, Jan, and Cristian Lorenz, eds. 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36441-9.

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14

Ehrhardt, Jan. 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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15

Hein, Gumlunter W. A model comparison in vertical crustal motion estimation using leveling data. Rockville, MD: National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services, 1986.

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16

Kuhn, Peter. Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-4474-3.

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17

Hein, Günter W. A model comparison in vertical crustal motion estimation using leveling data. Rockville, MD: National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services, 1986.

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18

Masanobu, Yamamoto, and National Research Council Canada. Division of Electrical Engineering., eds. Direct estimation of deformable motion parameters from a range image sequence. Ottawa, Ont: National Research Council Canada, Division of Electrical Engineering, 1990.

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19

New algorithms for variable time delay and nonuniform image motion estimation. Norwood, N.J: Ablex Pub. Corp., 1994.

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20

1931-, Saridis George N., and United States. National Aeronautics and Space Administration., eds. Distance estimation and collision prediction for on-line robotic motion planning. Troy, N.Y: Center for Intelligent Robotic Systems for Space Exploration, Rensselaer Polytechnic Institute, 1991.

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21

Bussiere, Colin. Intensity scale invariant motion estimation with rotation and spatial scaling information. Ottawa: National Library of Canada, 1993.

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22

Favaro, Paolo. 3-D shape estimation and image restoration: Exploiting defocus and motion blur. London: Springer, 2007.

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23

Zhou, Peifang. Application of Markov random field theory to image coding and motion estimation. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1993.

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24

Armstrong, Brian Stewart Randall. Dynamics for robot control: Friction modeling and ensuring excitation during parameter identification. Stanford, CA: Dept. of Computer Science, Stanford University, 1988.

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25

Iagnemma, Karl. Mobile robots in rough terrain: Estimation, motion planning, and control with application to planetary rovers. Berlin: Springer, 2010.

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26

Ishiguro, Tomiko. On high resolution schemes for three-dimensional Euler equations. I. Estimation of recent TVD schemes. Tokyo: National Aerospace Laboratory, 1987.

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27

Coelho, Alessandra Martins. Multimedia Networking and Coding: State-of-the Art Motion Estimation in the Context of 3D TV. Cyprus: INTECH, 2013.

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28

Kyun, Chung Wan, ed. Perturbation compensator based robust tracking control and state estimation of mechanical systems. Berlin: Springer, 2004.

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29

Leader, Daniel Eugene. Kalman filter estimation of underwater vehicle position and attitude using a Doppler velocity aided inertial motion unit. Springfield, Va: Available from National Technical Information Service, 1994.

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30

Sallinen, Mikko. Modelling and estimation of spatial relationships in sensor-based robot workcells. Espoo [Finland]: VTT Technical Research Centre of Finland, 2003.

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31

1961-, Choudhary Alok N., and United States. National Aeronautics and Space Administration., eds. Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings. Urbana, IL: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1990.

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32

G, Futamura Robert, Parker Donald E, and United States. National Aeronautics and Space Administration., eds. Inertial acceleration as a measure of linear vection: An alternative to magnitude estimation. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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33

Toro, Javier G. Direct and indirect parametric multiple motion estimation in image sequences and their application in layer-based angiographic image compression. [s.l: The Author], 2000.

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34

1961-, Choudhary Alok N., and United States. National Aeronautics and Space Administration., eds. Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system. Urbana, IL: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1990.

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35

United States. National Aeronautics and Space Administration., ed. Modeling visual, vestibular and oculomotor interactions in self-motion estimation: Final annual report for NAGW-4127, period covered--5/31/95 - 6/31/96. [Washington, DC: National Aeronautics and Space Administration, 1997.

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36

A, Paielli Russell, and Ames Research Center, eds. Direct inversion of rigid-body rotational dynamics. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1990.

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37

Bach, Ralph E. Direct inversion of rigid-body rotational dynamics. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1990.

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38

Ju, Xuan. Estimating time to contact by detecting and tracking motion boundaries. Ottawa: National Library of Canada, 1993.

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39

Archondo-Callao, Rodrigo. Estimating vehicle operating costs. Washington, D.C: World Bank, 1994.

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40

Miller, John S. Field validation of speed estimation techniques for air quality conformity analysis. Charlottesville, Va: Virginia Transportation Research Council, 2004.

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41

National Center for Health Statistics (U.S.). National Health and Nutrition Examination Survey: Estimation procedures, 2007-2010. Hyattsville, Maryland: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, 2013.

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42

Kivanc, Didem. Motion estimation. 1995.

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43

Hill, Lyndon. Motion estimation in video coding. 1995.

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44

Crinon, Regis. Adaptive model-based motion estimation. 1993.

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45

Crinon, Regis. Adaptive model-based motion estimation. 1993.

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46

Kalmoun, El Mostafa, Azizan Saaban, Haslinda Ibrahim, Razamin Ramli, and Zurni Omar. Multilevel Optimization for Dense Motion Estimation. UUM Press, 2012. http://dx.doi.org/10.32890/9789670474274.

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This monograph offers design for fast and reliable technique in the dense motion estimation. This Multilevel Optimization for Dense Motion Estimation work blends both theory and applications to equip reader with an understanding of basic concepts necessary to apply in solving dense motion in a sequence of images. Illustrating well-known variation models for dealing with optical flow estimation, this monograph introduces variation models with applications. A host of variation models are outlines such as Horn-Schunck model, Contrast Invariation Models and Models for Large Displacement. Special attention is also given to multilevel optimization techniques namely multiresolution and multigrid methods to improve the convergence of the global optimum when compared to using only one level resolution in the context of computer vision. This monograph is a robust resource that provides insightful introduction to the field of image processing with its theory and applications. Overall, Multilevel Optimization for Dense Motion Estimation is highly recommended for scientists and engineers for an excellent choice for references and self-study.
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47

Motion Estimation Algorithms for Video Compression. Springer, 2012.

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48

Multilevel Optimization for Dense Motion Estimation. Sintok, Kedah Darul Aman, Malaysia: Penerbit Universiti Utara Malaysia, 2012.

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49

Metkar, Shilpa, and Sanjay Talbar. Motion Estimation Techniques for Digital Video Coding. Springer, 2013.

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50

Motion Estimation Techniques For Digital Video Coding. Springer, India, Private Ltd, 2013.

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