Understanding Perspective and Image Formation: A Look into Geometry and Radiometry - Prof., Study notes of Computer Science

The relationship between images and the world properties they represent, focusing on geometry and radiometry. It delves into the history of image formation through cameras, discussing the concepts of vanishing points, perspective, and the role of parallel lines. Additionally, it touches upon the importance of understanding perspective in computer vision and image processing. Russell naughton's camera obscura and the works of leonardo da vinci are referenced to provide historical context.

Typology: Study notes

Pre 2010

Uploaded on 02/13/2009

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• Vision infers world properties form images.

• How do images depend on these properties?

• Two key elements

– Geometry

– Radiometry

– We consider only simple models of these

  • Used to observe eclipses (eg., Bacon, 1214-1294)
  • By artists (eg., Vermeer).

http://brightbytes.com/cosite/collection2.html (Jack and Beverly Wilgus)

Jetty at Margate England,

  • Abstract camera

model - box with a

small hole in it

  • Pinhole cameras

work in practice

(Forsyth & Ponce)

(Forsyth & Ponce)

  • Each set of parallel lines 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
  • Points project to points
  • Lines project to lines
  • Planes project to the whole image or a half image
  • Angles are not preserved
  • Degenerate cases
    • Line through focal point projects to a point.
    • Plane through focal point projects to line
    • Plane perpendicular to image plane projects to part of

the image (with horizon).

http://www.sanford-artedventures.com/create/tech_1pt_perspective.html

  • Cartesian coordinates:
    • We have, by similar

triangles, that

  • Ignore the third coordinate,

and get

z

y f z

x x y z f

z

y y f

z

x x f

( , , ) ( ' , ' , f ')

z

y

f

z

x

x y z f

  • s is constant for all points.
  • Parallel lines no longer converge, they remain

parallel.

• Weak perspective much simpler math.

– Accurate when object is small and distant.

– Most useful for recognition.

• Pinhole perspective much more accurate for

scenes.

– Used in structure from motion.

• When accuracy really matters, must model

real cameras.