Computer Vision - A Modern Approach

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Presentation transcript:

Computer Vision - A Modern Approach Cameras First photograph due to Niepce First on record shown in the book - 1822 Basic abstraction is the pinhole camera lenses required to ensure image is not too dark various other abstractions can be applied Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Pinhole cameras Abstract camera model - box with a small hole in it Pinhole cameras work in practice The point to make here is that each point on the image plane sees light from only one direction, the one that passes through the pinhole. Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Distant objects are smaller Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Parallel lines meet Common to draw film plane in front of the focal point. Moving the film plane merely scales the image. Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Vanishing points each set of parallel lines (=direction) meets at a different point The vanishing point for this direction Sets of parallel lines on the same plane lead to collinear vanishing points. The line is called the horizon for that plane Good ways to spot faked images scale and perspective don’t work vanishing points behave badly supermarket tabloids are a great source. Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Is this a perspective image of four identical buildings? why not? Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

The equation of projection Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

The equation of projection Cartesian coordinates: We have, by similar triangles, that (x, y, z) -> (f x/z, f y/z, -f) Ignore the third coordinate, and get Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Homogenous coordinates Add an extra coordinate and use an equivalence relation for 2D equivalence relation k*(X,Y,Z) is the same as (X,Y,Z) for 3D equivalence relation k*(X,Y,Z,T) is the same as (X,Y,Z,T) Basic notion Possible to represent points “at infinity” Where parallel lines intersect Where parallel planes intersect Possible to write the action of a perspective camera as a matrix Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach The camera matrix Turn previous expression into HC’s HC’s for 3D point are (X,Y,Z,T) HC’s for point in image are (U,V,W) Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Weak perspective Issue perspective effects, but not over the scale of individual objects collect points into a group at about the same depth, then divide each point by the depth of its group Adv: easy Disadv: wrong Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Orthographic projection Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

The projection matrix for orthographic projection Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Pinhole too big - many directions are averaged, blurring the image Pinhole too small- diffraction effects blur the image Generally, pinhole cameras are dark, because a very small set of rays from a particular point hits the screen. Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach The reason for lenses Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach The thin lens Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Spherical aberration Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Lens systems Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Vignetting Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Other (possibly annoying) phenomena Chromatic aberration Light at different wavelengths follows different paths; hence, some wavelengths are defocussed Machines: coat the lens Humans: live with it Scattering at the lens surface Some light entering the lens system is reflected off each surface it encounters (Fresnel’s law gives details) Machines: coat the lens, interior Humans: live with it (various scattering phenomena are visible in the human eye) Geometric phenomena (Barrel distortion, etc.) Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Camera parameters Issue camera may not be at the origin, looking down the z-axis extrinsic parameters one unit in camera coordinates may not be the same as one unit in world coordinates intrinsic parameters - focal length, principal point, aspect ratio, angle between axes, etc. Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Computer Vision - A Modern Approach Camera calibration Issues: what are intrinsic parameters of the camera? what is the camera matrix? (intrinsic+extrinsic) General strategy: view calibration object identify image points obtain camera matrix by minimizing error obtain intrinsic parameters from camera matrix Error minimization: Linear least squares easy problem numerically solution can be rather bad Minimize image distance more difficult numerical problem solution usually rather good, start with linear least squares Numerical scaling is an issue Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Geometric properties of projection Points go to points Lines go to lines Planes go to whole image Polygons go to polygons Degenerate cases line through focal point to point plane through focal point to line Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Polyhedra project to polygons (because lines project to lines) Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Junctions are constrained This leads to a process called “line labelling” one looks for consistent sets of labels, bounding polyhedra disadv - can’t get the lines and junctions to label from real images Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth

Curved surfaces are much more interesting Crucial issue: outline is the set of points where the viewing direction is tangent to the surface This is a projection of a space curve, which varies from view to view of the surface Computer Vision - A Modern Approach Set: Cameras Slides by D.A. Forsyth