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harris-100607074436-phpapp01

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Harris corner detector
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Page 1: harris-100607074436-phpapp01

Harris corner detector

Page 2: harris-100607074436-phpapp01

Moravec corner detector (1980)• We should easily recognize the point by looking through a small window• Shifting a window in any direction should give a large change in intensity

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Moravec corner detector

flat

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Moravec corner detector

flat

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Moravec corner detector

flat edge

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Moravec corner detector

flat edge cornerisolated point

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Moravec corner detectorChange of intensity for the shift [u,v]:

2

,

( , ) ( , ) ( , ) ( , )x y

E u v w x y I x u y v I x y

IntensityShifted intensityWindow function

Four shifts: (u,v) = (1,0), (1,1), (0,1), (-1, 1)Look for local maxima in min{E}

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Problems of Moravec detector• Noisy response due to a binary window function• Only a set of shifts at every 45 degree is considered• Responds too strong for edges because only minimum of E is taken into accountHarris corner detector (1988) solves these problems.

Page 9: harris-100607074436-phpapp01

Harris corner detectorNoisy response due to a binary window functionUse a Gaussian function

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Harris corner detectorOnly a set of shifts at every 45 degree is considered Consider all small shifts by Taylor’s expansion

yxyx

yxy

yxx

yxIyxIyxwC

yxIyxwB

yxIyxwA

BvCuvAuvuE

,

,

2

,

2

22

),(),(),(

),(),(

),(),(

2),(

Page 11: harris-100607074436-phpapp01

Harris corner detector

( , ) ,u

E u v u v Mv

Equivalently, for small shifts [u,v] we have a bilinear approximation:

2

2,

( , ) x x y

x y x y y

I I IM w x y

I I I

, where M is a 22 matrix computed from image derivatives:

Page 12: harris-100607074436-phpapp01

Harris corner detectorResponds too strong for edges because only minimum of E is taken into accountA new corner measurement

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Harris corner detector

( , ) ,u

E u v u v Mv

Intensity change in shifting window: eigenvalue analysis1, 2 – eigenvalues of M

direction of the slowest change

direction of the fastest change

(max)-1/2

(min)-1/2

Ellipse E(u,v) = const

Page 14: harris-100607074436-phpapp01

Harris corner detector

1

2

Corner1 and 2 are large,

1 ~ 2;

E increases in all directions

1 and 2 are small;

E is almost constant in all directions

edge 1 >> 2

edge 2 >> 1

flat

Classification of image points using eigenvalues of M:

Page 15: harris-100607074436-phpapp01

Harris corner detectorMeasure of corner response:

2det traceR M k M

1 2

1 2

dettrace

MM

(k – empirical constant, k = 0.04-0.06)

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Another view

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Another view

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Another view

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Summary of Harris detector

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Harris corner detector (input)

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Corner response R

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Threshold on R

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Local maximum of R

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Harris corner detector

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Harris Detector: Summary• Average intensity change in direction [u,v] can be expressed as a bilinear form:

• Describe a point in terms of eigenvalues of M:measure of corner response

• A good (corner) point should have a large intensity change in all directions, i.e. R should be large positive

( , ) ,u

E u v u v Mv

21 2 1 2R k


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