Presentation10(1) - Computer Vision Computer Lecture #10...

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Computer Vision Computer Vision Lecture #10 Lecture #10 Hossam Abdelmunim 1 2 1 Computer & Systems Engineering Department, Ain Shams University, Cairo, Egypt 2 Electerical and Computer Engineering Department, University of Louisville, Louisville, KY, USA ECE619/645 – Spring 2011
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Correspondence problem Three Questions What to match? Features: point, line, area, structure? – Where to search correspondence? Epipolar line? How to measure similarity? Depends on features Approaches Correlation-based approach Feature-based approach Advanced Topics Image filtering to handle illumination changes Adaptive windows to deal with multiple disparities Local warping to account for perspective distortion Sub-pixel matching to improve accuracy Self-consistency to reduce false matches Multi-baseline stereo
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Correlation Approach For Each point (x l , y l ) in the left image, define a window centered at the point (x l , y l ) LEFT IMAGE
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Correlation Approach … search its corresponding point within a search region in the right image (x l , y l ) RIGHT IMAGE
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Correlation Approach … the disparity (dx, dy) is the displacement when the correlation is maximum (x l , y l ) dx (x r , y r ) RIGHT IMAGE
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Correlation Approach Elements to be matched Image window of fixed size centered at each pixel in the left image Similarity criterion A measure of similarity between windows in the two images The corresponding element is given by window that maximizes the similarity criterion within a search region
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Presentation10(1) - Computer Vision Computer Lecture #10...

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