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Segmentation given partial grouping constraints (2004)
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| Venue: | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Citations: | 80 - 4 self |
BibTeX
@ARTICLE{Yu04segmentationgiven,
author = {Stella X. Yu and Ieee Computer Society and Jianbo Shi and Ieee Computer Society},
title = {Segmentation given partial grouping constraints},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2004},
pages = {173--183}
}
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Abstract
Abstract—We consider data clustering problems where partial grouping is known a priori. We formulate such biased grouping problems as a constrained optimization problem, where structural properties of the data define the goodness of a grouping and partial grouping cues define the feasibility of a grouping. We enforce grouping smoothness and fairness on labeled data points so that sparse partial grouping information can be effectively propagated to the unlabeled data. Considering the normalized cuts criterion in particular, our formulation leads to a constrained eigenvalue problem. By generalizing the Rayleigh-Ritz theorem to projected matrices, we find the global optimum in the relaxed continuous domain by eigendecomposition, from which a near-global optimum to the discrete labeling problem can be obtained effectively. We apply our method to real image segmentation problems, where partial grouping priors can often be derived based on a crude spatial attentional map that binds places with common salient features or focuses on expected object locations. We demonstrate not only that it is possible to integrate both image structures and priors in a single grouping process, but also that objects can be segregated from the background without specific object knowledge. Index Terms—Grouping, image segmentation, graph partitioning, bias, spatial attention, semisupervised clustering, partially labeled classification. æ
Keyphrases
partial grouping constraint image segmentation constrained optimization problem eigenvalue problem relaxed continuous domain discrete labeling problem common salient feature unlabeled data partial grouping cue data clustering problem object location rayleigh-ritz theorem index term grouping partial grouping prior graph partitioning global optimum specific object knowledge structural property near-global optimum data point real image segmentation problem spatial attention cut criterion crude spatial attentional map partial grouping image structure single grouping process
