Measuring the Ecological Statistics of Figure-Ground Charless Fowlkes, David Martin, Jitendra Malik

Measuring the Ecological Statistics of

Figure-Ground

Charless Fowlkes, David Martin, Jitendra Malik

Is there an Ecological Justification for Figure-Ground Cues?

• Size

• Surroundedness

• Convexity

• Lower-Region

• Symmetry

• …

Are figural regions in the natural world really more convex?

Figure-Ground Labeling

200 images each labeled by 2 subjects

Consistency – 88% agreement

Agreement doesn’t differ with edge length

Local Figural Assignment Cues

• Size and Surroundedness [Rubin 1915]

• Convexity [Metzger,Kanizsa]

• Lower-Region [Vecera, Vogel & Woodman 2002]

Size(p) = log(AF / AG)

Size :

GFp

Convexity(p) = log(CF / CG)

Convexity:

Convexity:

Aboveness(p) = cos()

Aboveness:

center of mass

Empirical Frequencies of Size, Convexity and Aboveness.

1200 sample points per image

Local Boundary Detection in Natural Images: Matching Human

and Machine Performance

Dave Martin, Charless Fowlkes, Laura Walker, Jitendra Malik

Boundary Detection

ImageBoundary Cues

Model

Pb

Challenges: texture cue, cue combination Goal: learn the posterior probability of a boundary Pb(x,y,) from local information only

Cue CombinationBrightness

Color

Texture

Non-Boundaries Boundaries

T

B

C

Two Decades of Boundary

Detection

Local Boundary Detection Solved?

Clearly top-down, high level knowledge is utilized by humans

Test Humans on Local Patches

Test Humans on Local Patches

Test Humans on Local Patches

Did you see a boundary running through the center

of the patch? [Y/N]

radius: 9, 18, 36humans: 78, 83, 85

F-Measure at r = 9Humans: 78

Machines: 78