2013 · 15 citations · 10 references
CartographySupport Vector MachineMachine VisionImage AnalysisData ScienceData MiningPattern RecognitionSkyline LocalizationSky RegionGeographyIncomplete FragmentsEngineeringVehicle LocalizationGeospatial MappingComputer ScienceLocalizationSocial SciencesSpatial Verification
In this paper, we propose a novel method for automatically locating the skyline that represents the shape of mountains. The appearances of mountain and sky are variable because of the weather, season or region. In order to extract the skyline of mountains under complicated and variable circumstances, support vector machine (SVM) is applied for the prediction of a part of the skyline between sky region and mountain region by using the color, statistics features and location information of edge. Then, the linking of incomplete fragments of skyline is formulated as a shortest path problem and solved by dynamic programming strategy. Our experimental results demonstrate that the proposed method is accurate and robust.
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Chih-Chung Chang, Chih‐Jen Lin · ACM Transactions on Intelligent Systems and Technology · 2011 · 41.1K citations
Data Classification, Support Vector Machine, Classification Method +15
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Shai Avidan, Ariel Shamir · 2007 · 1.4K citations
Seam carving for content-aware image resizing
Shai Avidan, Ariel Shamir · ACM Transactions on Graphics · 2007 · 1.1K citations
Ying Song, Xin Tong, Fabio Pellacini et al. · ACM Transactions on Graphics · 2009 · 136 citations · Full text