2. ?

3. White
Fuzzy
Color
Oblong
Texture
Shape

4. Most problems in vision are underconstrained
White
Color
Most problems in vision are underconstrained

5. The goal of computational vision:
To identify and formalize the strategies and
assumptions the visual system uses to overcome
under-constrainedness.

6. The goal of computational vision:
To identify and formalize the strategies and
assumptions the visual system uses to overcome
under-constrainedness.
David Marr

7. Processing Framework Proposed by Marr
Recognition
3D structure; motion characteristics; surface properties
Shape
From
stereo
Motion
flow
Shape
From
motion
Color
estimation
Shape
From
contour
Shape
From
shading
Shape
From
texture
Edge extraction
Emphasis on
‘Bottom-up’
processing
Image

8. My research interests Image Recognition Edge extraction TANGENT ALERT!
Mechanisms
of recognition
‘Top-down’
Influences on
perception
Shape
From
stereo
Motion
flow
Shape
From
motion
Color
estimation
Shape
From
contour
Shape
From
shading
Shape
From
texture
Edge extraction
Image

9. The importance of edges
Depth discontinuity
(Object border)
Orientation change
(Object shape)
Reflectance change
(Object property)

10. What is an edge?
- a point at which image luminance (I) changes steeply
- a point at which the first derivative of I has a peak

11. Detecting edges Grid of numbers Denoting edge Strength at each
Point in image
Edge map
Thresholding
Convolution
(dot-products all
over the image)
Edge
operator 1
Image
Network implementation of convolution

12. What is an edge?
- a point at which image luminance (I) changes steeply
- a point at which the first derivative of I has a peak
- a point at which the second derivative of I has a zero crossing

13. Second order differential operators
Image
A B C D
First
differences
(A-B) (B-C) (C-D)
Second
differences
(A-2B+C) (B-2C+D)
Why would we want to use second order
Operators rather than first order ones?

14. Second order differential operators
Image
A B C D
First
differences
(A-B) (B-C) (C-D)
Second
differences
(A-2B+C) (B-2C+D)
Zero crossings can
Be detected with
Circularly symmetric
Filters!
(orientation
Independence)

15. The link between models of edge detection and physiology

17. Detecting edges at different scales

18. The scale integration problem

19. The scale integration problem
Witkin, 1983

20. Detecting illusory contours
Where do conventional edge-detectors fail?
Detecting illusory contours
No luminance difference across
long sections of the perceived contours