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Efficient Structured Support Vector Regression

Jia, Ke; Wang, Lei; Liu, Nianjun


Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structured support vector regression framework by extending the max-margin principle to incorporate spatial correlations among neighboring pixels. The objective function in our framework considers both label information and pairwise features, helping to achieve better cross-smoothing over neighboring nodes. With the bundle...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
Source: Proceedings of the International Image and Vision Computing New Zealand Conference (IVCNZ 2010)
DOI: 10.1007/978-3-642-19318-7_46


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