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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Co-Sparse Textural Similarity for Interactive Segmentation
verfasst von : Claudia Nieuwenhuis, Simon Hawe, Martin Kleinsteuber, Daniel Cremers
Erschienen in: Computer Vision – ECCV 2014
Verlag: Springer International Publishing
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We propose an algorithm for segmenting natural images based on texture and color information, which leverages the co-sparse analysis model for image segmentation. As a key ingredient of this method, we introduce a novel textural similarity measure, which builds upon the co-sparse representation of image patches. We propose a statistical MAP inference approach to merge textural similarity with information about color and location. Combined with recently developed convex multilabel optimization methods this leads to an efficient algorithm for interactive segmentation, which is easily parallelized on graphics hardware. The provided approach outperforms state-of-the-art interactive segmentation methods on the Graz Benchmark.