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Multi-Scale Contour Extraction Based on Natural Image Statistics. Francisco J. Estrada and James H. Elder. 5th IEEE Computer Society Workshop on Perceptual Organization in Computer Vision. Centre for Vision Research. Finding object boundaries… How Hard Can It Be?.
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Multi-Scale Contour Extraction Based on Natural Image Statistics Francisco J. Estrada and James H. Elder 5th IEEE Computer Society Workshopon Perceptual Organization in Computer Vision Centre for Vision Research
Finding object boundaries… How Hard Can It Be? The search-space is very large
Finding object boundaries… How Hard Can It Be? The search-space is very large Local structure can easily dominate
Proximity • Good continuation • Similarity Probabilistic Grouping • Estimate grouping probability • Use natural scene statistics • Gestalt grouping cues
Probabilistic Grouping • Probability distributions
Relate pairs of consecutive tangents Provide a prior for grouping Probabilistic Grouping • Constructive algorithm • Expand • Prune
Input tangents Coarse-scale contour Spatial prior Spatial Prior
Coarse-scale contour Noisy, irregular Fourier Descriptor Spatial Prior
Coarse-scale contour Smooth Fourier contour Project to fine scale Spatial Prior
Spatial Prior • Measure: • - Distance from Fourier contour • - Difference in angle
Input tangents Boundary Energy (Martin et al. 2002) P(grouped|BE) Boundary Energy • Additional object cue
(*) Using the geometric mean Algorithm Summary • Group at coarsest scale Repeat: • Select the N contours to refine (*) • Group at fine scale using spatial prior • Additional run without spatial prior
Experimental Results • 20 images from the BSD • Results reported for: • * (GND) Ground-truth • * (MS) Multi-scale grouping • * (SS) Single-scale grouping • * (RC) Ratio Contour (Wang et al. 2005) • * (EJ) Heuristic search (Estrada & Jepson 2004)
Detected Overlay Ground-Truth Error = + Error Measure for Comparison
Further considerations • Use of appearance information (colour, texture, etc.) • Contour selection • Use of prior shape models • Improve evaluation framework