1 P. Arbelaez, M. Maire, C. Fowlkes, J. Malik. Contour Detection and Hierarchical image...
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1 P. Arbelaez, M. Maire, C. Fowlkes, J. Malik. Contour Detection and Hierarchical image Segmentation. IEEE Trans. on PAMI, 2011. Student: Hsin-Min Cheng
1 P. Arbelaez, M. Maire, C. Fowlkes, J. Malik. Contour
Detection and Hierarchical image Segmentation. IEEE Trans. on PAMI,
2011. Student: Hsin-Min Cheng Advisor: Sheng-Jyh Wang
Contour Detection 1. Learn local boundary cues 2. Global
framework to capture closure, continuity 3. Local Cues and global
cues combination 8
Slide 9
Learn local boundary cues Image Local Boundary Cues Model
Brightness Color Texture Cue Combination Contour Detection 9
Slide 10
Learn local boundary cues Brightness L*a*b* colorspace Color
L*a*b* colorspace Texture Convolve with 17 filters Filters for
creating textons 10 Contour Detection
Slide 11
11 Learn local boundary cues Oriented gradient of histograms
Example Gradient magnitude G at location(x, y) Three scales of r 11
Contour Detection ure
Slide 12
12 Learn local boundary cues Local Cues Combination 12 Contour
Detection ure
Slide 13
Global framework to capture closure, continuity Contour
Detection 13 V:image pixels E:connections between pairs of nearby
pixels =>Build a weighted graph G=(V,E) from image
Slide 14
Global framework to capture closure, continuity Contour
Detection 14
Slide 15
Local Cues and global cues combination Contour Detection 15
Local CuesGlobal cues
Conclusion A high performance contour detector, combining local
and global image information A method to transform any contour
detector signal into a hierarchy of regions while preserving
contour quality 30
Slide 31
Reference P. Arbelaez, M. Maire, C. Fowlkes and J. Malik.
Contour Detection and Hierarchical Image Segmentation. IEEE TPAMI,
Vol. 33, No. 5, pp. 898-916, May 2011 P. Arbelaez, M. Maire, C.
Fowlkes and J. Malik. From Contours to Regions: An Empirical
Evaluation. In CVPR 2009. P. Arbelaez and L. Cohen. Constrained
Image Segmentation from Hierarchical Boundaries. In CVPR 2008.
31
Region benchmarks(1) Segment Covering Probabilistic Rand Index
[Unnikrishnan et. al. 07] [Yang et. al. 08] Variation of
Information [Meila 05] Distance Between two segmentations in terms
of their average conditional entropy given by 34
Slide 35
Region benchmarks(2) CoveringRand Index Variation of
Information 35