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Computer Vision Lecture #2 Hossam Abdelmunim 1 & Aly A. Farag 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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Geometric Primitives and Transformations 2D Point – x=(x1,x2,1) 2D Line – ax1+bx2+c=0
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Geometric Primitives and Transformations 3D Point – x=(x1,x2,x3,1) 3D Line Derive the line equation shown above.
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Geometric Primitives and Transformations 3D Plane –ax+by+cz+d=0; Derive the plane equation shown above.
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Transformation Matrix Translation (Example in 2D)
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Transformation Matrix Rotation Matrix (Example in 2D)
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Transformation Matrix Scaling Matrix (Example in 3D)
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Projective Transformation Matrix
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Hierarchy of Coordinate Transformations *Homogeneous Scaling, rotation, and translation *
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3D to 2D Projection
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What do we need? we need to specify how 3D primitives (points) are projected onto the image plane. We can do this using a linear 3D to 2D projection matrix.
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ExampleExample
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Geometric Interpretation Perspective v's Parallel (orthogonal) Projection
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Perspective Projection Matrix Equation
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Para-Perspective Projection
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