Landmark-Based Image Analysis: Using Geometric and Intensity ModelsLandmarks are preferred image features for a variety of computer vision tasks such as image mensuration, registration, camera calibration, motion analysis, 3D scene reconstruction, and object recognition. Main advantages of using landmarks are robustness w. r. t. lightning conditions and other radiometric vari ations as well as the ability to cope with large displacements in registration or motion analysis tasks. Also, landmark-based approaches are in general com putationally efficient, particularly when using point landmarks. Note, that the term landmark comprises both artificial and natural landmarks. Examples are comers or other characteristic points in video images, ground control points in aerial images, anatomical landmarks in medical images, prominent facial points used for biometric verification, markers at human joints used for motion capture in virtual reality applications, or in- and outdoor landmarks used for autonomous navigation of robots. This book covers the extraction oflandmarks from images as well as the use of these features for elastic image registration. Our emphasis is onmodel-based approaches, i. e. on the use of explicitly represented knowledge in image analy sis. We principally distinguish between geometric models describing the shape of objects (typically their contours) and intensity models, which directly repre sent the image intensities, i. e. ,the appearance of objects. Based on these classes of models we develop algorithms and methods for analyzing multimodality im ages such as traditional 20 video images or 3D medical tomographic images. |
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Contenido
II | 1 |
III | 4 |
IV | 7 |
V | 13 |
VI | 16 |
VII | 19 |
VIII | 21 |
IX | 26 |
XLI | 109 |
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L | 156 |
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XXXIV | 84 |
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XXXVIII | 100 |
XXXIX | 102 |
XL | 106 |
LI | 168 |
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LIII | 171 |
LIV | 172 |
LV | 176 |
LVI | 179 |
LVII | 183 |
LIX | 186 |
LX | 188 |
LXI | 191 |
LXII | 198 |
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LXVI | 206 |
LXVII | 211 |
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LXX | 221 |
LXXI | 224 |
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LXXIV | 241 |
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LXXVII | 255 |
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Otras ediciones - Ver todas
Landmark-Based Image Analysis: Using Geometric and Intensity Models Karl Rohr Vista previa limitada - 2013 |
Landmark-Based Image Analysis: Using Geometric and Intensity Models Karl Rohr Sin vista previa disponible - 2010 |
Landmark-Based Image Analysis: Using Geometric and Intensity Models Karl Rohr Sin vista previa disponible - 2012 |
Términos y frases comunes
3D images accuracy Actually additional affine transformation algorithms analytic anatomical applied approach approximation assume basis bound characterization combination comparison computer vision consider contour corner corresponding curvature curve defined deformations denoted depends described detection determine differential direction directly edge elastic equation errors estimated et al example extraction Figure fitting function Gaussian geometric given hand horn human brain image analysis image registration important intensity interpolation introduced invariants knowledge L-corner localization localization uncertainty matching mathematical matrix mean measure Medical Imaging method minimal noise normal Note objects obtain operators orientation parameters partial derivatives particularly performance physical point landmarks position possible precision principal problem Proc procedure Processing properties Recognition region represent result Rohr scheme shown slices solution step structures surface task term theory thin-plate splines transformation types values visualization weights
Pasajes populares
Página 282 - Maciunas, RJ, and Fitzpatrick, JM, "Registration of head CT images to physical space using a weighted combination of points and surfaces," IEEE Transactions on Medical Imaging, 17, pp.
Página 268 - Medical Image Analysis: Progress over Two Decades and the Challenges Ahead," IEEE Transactions on Pattern Analysis and Machine Intelligence 22, pp.
Página 296 - New feature points based on geometric invariants for 3D image registration," International Journal of Computer Vision 18, pp.
Página 283 - JV Miller, DE Breen, WE Lorensen, RM O'Bara, and MJ Wozny. Geometrically Deformed Models: A method for extracting closed geometric models from volume data.
Página 283 - On the problem of geometric distortion in Magnetic Resonance Images for Stereotactic Neurosurgery,
Página 280 - Distortion invariant object recognition in the dynamic link architecture", IEEE Trans, on Computers, vol.
Referencias a este libro
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial ... Arthur Ardeshir Goshtasby Vista previa limitada - 2005 |
Precision Landmark Location for Machine Vision and Photogrammetry: Finding ... José A. Gutierrez,Brian S.R. Armstrong Vista previa limitada - 2007 |