Low-Rank Affinity Based Local-Driven Multilabel Propagation
Joint Authors
Li, Teng
Cheng, Bin
Wu, Jun
Wu, Xinyu
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-21
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
This paper presents a novel low-rank affinity based local-driven algorithm to robustly propagate the multilabels from training images to test images.
A graph is constructed over the segmented local image regions.
The labels for vertices from the training data are derived based on the context among different training images, and the derived vertex labels are propagated to the unlabeled vertices via the graph.
The multitask low-rank affinity, which jointly seeks the sparsity-consistent low-rank affinities from multiple feature matrices, is applied to compute the edge weights between graph vertices.
The inference process of multitask low-rank affinity is formulated as a constrained nuclear norm and ℓ2,1-norm minimizationproblem.
The optimization is conducted efficiently with the augmented Lagrange multiplier method.
Based on the learned local patch labels we can predict the multilabels for the test images.
Experiments on multilabel image annotation demonstrate the encouraging results from the proposed framework.
American Psychological Association (APA)
Li, Teng& Cheng, Bin& Wu, Xinyu& Wu, Jun. 2013. Low-Rank Affinity Based Local-Driven Multilabel Propagation. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1031804
Modern Language Association (MLA)
Li, Teng…[et al.]. Low-Rank Affinity Based Local-Driven Multilabel Propagation. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1031804
American Medical Association (AMA)
Li, Teng& Cheng, Bin& Wu, Xinyu& Wu, Jun. Low-Rank Affinity Based Local-Driven Multilabel Propagation. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1031804
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1031804