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

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Presentation transcript:

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(A F / A G ) Size : G F p

Convexity(p) = log(C F / C G ) Convexity:

Aboveness(p) = cos(  ) Aboveness:  center of mass

Empirical Frequencies of Size, Convexity and Aboveness sample points per image

Learning Segmentation From Common-Fate, or not? Charless Fowlkes, Dave Martin

Benchmark Image Estimated Affinity (W) Edge Cues Region Cues Learning Similarity Cues Human Segmentations Groundtruth Affinity (S) Segment

Learning Segmentation From Common Fate? Infants group by common fate before they learn other static similarity cues. DVDs provide huge quantity of easily accessible data but no ground-truth segmentations.

Learning Segmentation From Common Fate? Track points using Lucas-Kanade Cluster into 2 motion groups Transfer groups to image pixels and use as ground truth for pairwise affinity cues.

Local Boundary Detection in Natural Images: Matching Human and Machine Performance Dave Martin, Charless Fowlkes, Laura Walker, Jitendra Malik

Boundary Detection Image Boundary Cues Model PbPb Challenges: texture cue, cue combination Goal: learn the posterior probability of a boundary P b (x,y,  ) from local information only Cue Combination Brightness Color Texture

Non-BoundariesBoundaries T BC

Two Decades of Boundary Detection

Local Boundary Detection Solved? Clearly top-down, high level knowledge is utilized by humans

Test Humans on Local Patches

Did you see a boundary running through the center of the patch? [Y/N]

radius: 9, 18, 36 humans: 78, 83, 85 F-Measure at r = 9 Humans: 78 Machines: 78