A unified contour-pixel model for figure-ground segmentation

Ben Packer*, Stephen Gould, Daphne Koller

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


The goal of this paper is to provide an accurate pixel-level segmentation of a deformable foreground object in an image. We combine state-of-the-art local image segmentation techniques with a global object-specific contour model to form a coherent energy function over the outline of the object and the pixels inside it. The energy function includes terms from a variant of the TextonBoost method, which labels each pixel as either foreground or background. It also includes terms over landmark points from a LOOPS model [1], which combines global object shape with landmark-specific detectors. We allow the pixel-level segmentation and object outline to inform each other through energy potentials so that they form a coherent object segmentation with globally consistent shape and appearance. We introduce an inference method to optimize this energy that proposes moves within the complex energy space based on multiple initial oversegmentations of the entire image. We show that this method achieves state-of-the-art results in precisely segmenting articulated objects in cluttered natural scenes.

Original languageEnglish
Title of host publicationComputer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings
PublisherSpringer Verlag
Number of pages14
EditionPART 5
ISBN (Print)3642155545, 9783642155543
Publication statusPublished - 2010
Externally publishedYes
Event11th European Conference on Computer Vision, ECCV 2010 - Heraklion, Crete, Greece
Duration: 10 Sept 201011 Sept 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 5
Volume6315 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th European Conference on Computer Vision, ECCV 2010
CityHeraklion, Crete


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