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Computer Vision |
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12h L / 1 OE / 2 ECTS credits in common with IIC_AIA1 et IIC_AIA3 / IIC_AIA2 |
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Marie-Odile BERGER |
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Introduction |
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What is a computer vision system? Image modalities. Some examples of industrial computer vision. Open issues in computer vision.
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Low level processing |
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Edge detectors- curve detection: the active contour model- Extracting and matching interest points.
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3D Reconstruction |
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Stereovision: the projective matrix, the calibration task, the epipolar constraint, the correspondence problem for stereovision- Multiple camera systems-Volumetric scene reconstruction: space carving- Reconstruction from non-calibrated image sequences-Depth measurement using projected grid methods.
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Sequence analysis |
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Tracking methods: optic flow based methods, learning based methods- Recovering 3D information from video sequences- Tracking methods for medical imaging.
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Augmented reality |
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Introduction to augmented reality. Human Perceptions and Mixed Environments. Tracking requirements for augmented environments. Markerless tracker for AR. Application Domains of AR. Remaining challenges.
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References
D. Forsith et J. Ponce, Computer vision : a modern approach, Prentice Hall, 2002.
I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2000.
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| Last update 06/07/2007 by Cl.M. |
