Image Processing and Analysis Owen Carmichael
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- Technology
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This course deals with the techniques for automated extraction of high-level information from images generated by cameras, three-dimensional surface sensors, and medical devices. Typical applications include automated construction of 3D models from video footage and detection of objects in various types of images.
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Medical Image Acquisition
Lecture 20: Carmichael discusses three main ways of obtaining medical imaging data: CT (Computed Tomography) scans, MRIs (Magnetic Resonance Imaging) and PET (Positron Emission Tomography)
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Object Detection from Range Data
Lecture 19: Carmichael discusses some problems that can arise in range data-based detection and how these problems can be fixed by creating transformation-consistent clusters.
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Local Shape Representations
Lecture 18: Carmichael discusses advantages of local shape representations and two methods for creating them: the segmentation method and the vertex-based method.
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Global Shape Representations
Lecture 17: The instructor discusses ways of storing and searching 3D models. Explains database querying, geons, object signatures and shape histograms.
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Combining Multiple Meshes
Lecture 16: Carmichael discusses two approaches (mesh-based and volumetric) for combining multiple meshes to form a single closed surface.
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Mesh Alignment II
Lecture 15: In the second lecture on mesh alignment, Carmichale explains nonrigid alignment and how to accomplish this process using a technique called deformable registration.