The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

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The Camera 15-463: Computational Photograph Alexei Efros, CMU, Fall 200
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Transcript of The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Page 1: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

The Camera

15-463: Computational PhotographyAlexei Efros, CMU, Fall 2008

Page 2: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

How do we see the world?

Let’s design a camera• Idea 1: put a piece of film in front of an object• Do we get a reasonable image?

Slide by Steve Seitz

Page 3: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Pinhole camera

Add a barrier to block off most of the rays• This reduces blurring• The opening known as the aperture• How does this transform the image?

Slide by Steve Seitz

Page 4: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Pinhole camera model

Pinhole model:• Captures pencil of rays – all rays through a single point• The point is called Center of Projection (COP)• The image is formed on the Image Plane• Effective focal length f is distance from COP to Image Plane

Slide by Steve Seitz

Page 5: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Point of observation

Figures © Stephen E. Palmer, 2002

Dimensionality Reduction Machine (3D to 2D)

3D world 2D image

What have we lost?• Angles• Distances (lengths)

Page 6: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Funny things happen…

Page 7: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Parallel lines aren’t…

Figure by David Forsyth

Page 8: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Lengths can’t be trusted...

Figure by David Forsyth

B’

C’

A’

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…but humans adopt!

http://www.michaelbach.de/ot/sze_muelue/index.html

Müller-Lyer Illusion

We don’t make measurements in the image plane

Page 10: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Modeling projection

The coordinate system• We will use the pin-hole model as an approximation

• Put the optical center (Center Of Projection) at the origin

• Put the image plane (Projection Plane) in front of the COP– Why?

• The camera looks down the negative z axis– we need this if we want right-handed-coordinates

Slide by Steve Seitz

Page 11: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Modeling projection

Projection equations• Compute intersection with PP of ray from (x,y,z) to COP

• Derived using similar triangles (on board)

• We get the projection by throwing out the last coordinate:

Slide by Steve Seitz

Page 12: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Homogeneous coordinates

Is this a linear transformation?

Trick: add one more coordinate:

homogeneous image coordinates

homogeneous scene coordinates

Converting from homogeneous coordinates

• no—division by z is nonlinear

Slide by Steve Seitz

Page 13: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Perspective ProjectionProjection is a matrix multiply using homogeneous coordinates:

divide by third coordinate

This is known as perspective projection• The matrix is the projection matrix• Can also formulate as a 4x4

divide by fourth coordinateSlide by Steve Seitz

Page 14: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Orthographic Projection

Special case of perspective projection• Distance from the COP to the PP is infinite

• Also called “parallel projection”• What’s the projection matrix?

Image World

Slide by Steve Seitz

Page 15: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Spherical Projection

What if PP is spherical with center at COP?

In spherical coordinates, projection is trivial:

dNote: doesn’t depend on focal length d!

Page 16: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Building a real camera

Page 17: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Camera Obscura

The first camera• Known to Aristotle• Depth of the room is the effective focal length

Camera Obscura, Gemma Frisius, 1558

Page 19: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Shrinking the aperture

Why not make the aperture as small as possible?• Less light gets through• Diffraction effects…

Less light gets through

Slide by Steve Seitz

Page 20: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Shrinking the aperture

Page 21: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

The reason for lenses

Slide by Steve Seitz

Page 22: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Focus

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Focus and Defocus

A lens focuses light onto the film• There is a specific distance at which objects are “in focus”

– other points project to a “circle of confusion” in the image

• Changing the shape of the lens changes this distance

“circle of confusion”

Slide by Steve Seitz

Page 24: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Thin lenses

Thin lens equation:

• Any object point satisfying this equation is in focus• What is the shape of the focus region?• How can we change the focus region?• Thin lens applet: http://www.phy.ntnu.edu.tw/java/Lens/lens_e.html (by Fu-Kwun Hwang )

Slide by Steve Seitz

Page 25: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Varying Focus

Ren Ng

Page 26: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Depth Of Field

Page 27: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Depth of Field

http://www.cambridgeincolour.com/tutorials/depth-of-field.htm

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Aperture controls Depth of Field

Changing the aperture size affects depth of field• A smaller aperture increases the range in which the object is

approximately in focus• But small aperture reduces amount of light – need to

increase exposure

Page 29: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Varying the aperture

Large apeture = small DOF Small apeture = large DOF

Page 30: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Nice Depth of Field effect

Page 31: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Field of View (Zoom)

Page 32: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Field of View (Zoom)

Page 33: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Field of View (Zoom)

Page 34: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

f

FOV depends of Focal Length

Smaller FOV = larger Focal Length

f

Page 35: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

From Zisserman & Hartley

Page 36: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Field of View / Focal Length

Large FOV, small fCamera close to car

Small FOV, large fCamera far from the car

Page 37: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Fun with Focal Length (Jim Sherwood)

http://www.hash.com/users/jsherwood/tutes/focal/Zoomin.mov

Page 38: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Lens Flaws

Page 39: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Lens Flaws: Chromatic AberrationDispersion: wavelength-dependent refractive index

• (enables prism to spread white light beam into rainbow)

Modifies ray-bending and lens focal length: f()

color fringes near edges of image

Corrections: add ‘doublet’ lens of flint glass, etc.

Page 40: The Camera 15-463: Computational Photography Alexei Efros, CMU, Fall 2008.

Chromatic Aberration

Near Lens CenterNear Lens Center Near Lens Outer EdgeNear Lens Outer Edge

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Radial Distortion (e.g. ‘Barrel’ and ‘pin-cushion’)

straight lines curve around the image center

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Radial Distortion

Radial distortion of the image• Caused by imperfect lenses• Deviations are most noticeable for rays that pass through

the edge of the lens

No distortion Pin cushion Barrel

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Radial Distortion