Humans and animals have a number of senses

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Presentation transcript:

Humans and animals have a number of senses Sight Hearing Touch Smell Taste Balance Echolocation: bats, electric fields: sharks, compass: birds

Vision

Hearing

Echolocation of bats

Electric field sensing

Magnetic field sensing

Vision: most powerful sense Essential for survival: finding food, avoiding being food, finding mates Long range sensing: beyond our fingertip (vision is our way to touch the world)

Evolution of the eye ½ billion years

Climbing mount improbable 10 different designs

A plethora of eyes

Complex Eyes

Compound eyes

Human Eyes

Two kinds of eyes at the top: Camera type or planar Spherical

Many cameras in the market

Catadioptric – panoramic images

How does Vision work? Ancient Greeks: Extramission Theory

Descartes got it right

Many theories over the centuries The Gestaltists Von Helmholz: Unconscious inference David Marr: A reconstruction process that tells us where is what.

Theories influenced by the zeitgeist

Animal perception is active

Measuring eye movements

Robots with Vision

PR2 Humanoid

Perception for Robots 3 major problems Reconstruction Reorganization Recognition

Reconstruction

Reorganization: segmentation

Reorganization: flow

Recognition

Images and Videos Contain Lines (contours, edges) Intensity and Color Texture movement

Lines

Color, Texture

Motion

A theoretical model of an eye Pick a point in space and the light rays passing through O

Then cut the rays with a plane This gives an image O

Pinhole cameras Abstract camera model - box with a small hole in it Pinhole cameras work in practice (Forsyth & Ponce)

If we change the plane, we get an new image

How are these images related? (what remains invariant?)

Conics

Projection of circle

Vanishing points Vanishing point projection of a point at infinity image plane vanishing point camera center ground plane Vanishing point projection of a point at infinity

Vanishing points (2D) image plane vanishing point camera center line on ground plane

Vanishing points Properties image plane vanishing point V line on ground plane camera center C line on ground plane Properties Any two parallel lines have the same vanishing point v The ray from C through v is parallel to the lines An image may have more than one vanishing point

Parallelism (angles) not invariant

Cross ratio = only invariant

Back to our question: how are the 2 images related to each other Can we find a map, a function mapping x’ to x?

Fundamental Theorem: If we know how 4 points map to each other in the two planes, then we know how all points map. (if aA, bB, cC,dD, then we can map any point)

Proof B b a p A P c C s S d D

The projective plane Why do we need homogeneous coordinates? represent points at infinity, homographies, perspective projection, multi-view relationships What is the geometric intuition? a point in the image is a ray in projective space image plane (x,y,1) y (sx,sy,s) (0,0,0) x z Each point (x,y) on the plane is represented by a ray (sx,sy,s) all points on the ray are equivalent: (x, y, 1)  (sx, sy, s)

Projective lines What does a line in the image correspond to in projective space? A line is a plane of rays through origin all rays (x,y,z) satisfying: ax + by + cz = 0 A line is also represented as a homogeneous 3-vector l l p

Point and line duality A line l is a homogeneous 3-vector It is  to every point (ray) p on the line: l p=0 l l1 l2 p p2 p1 What is the line l spanned by rays p1 and p2 ? l is  to p1 and p2  l = p1  p2 l is the plane normal What is the intersection of two lines l1 and l2 ? p is  to l1 and l2  p = l1  l2 Points and lines are dual in projective space given any formula, can switch the meanings of points and lines to get another formula

Ideal points and lines Ideal point (“point at infinity”) Ideal line l  (a, b, 0) – parallel to image plane (a,b,0) y x z image plane (sx,sy,0) y x z image plane Ideal point (“point at infinity”) p  (x, y, 0) – parallel to image plane It has infinite image coordinates Corresponds to a line in the image (finite coordinates)

Fundamental Theorem (homography or collineation)

Projective vs Affine

Rectification