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conference paper
Superpixels and Polygons using Simple Non-Iterative Clustering
2017
30Th Ieee Conference On Computer Vision And Pattern Recognition (Cvpr 2017)
We present an improved version of the Simple Linear Iterative Clustering (SLIC) superpixel segmentation. Unlike SLIC, our algorithm is non-iterative, enforces connectivity from the start, requires lesser memory, and is faster. Relying on the superpixel boundaries obtained using our algorithm, we also present a polygonal partitioning algorithm. We demonstrate that our superpixels as well as the polygonal partitioning are superior to the respective state-of-the-art algorithms on quantitative benchmarks.
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main.pdf
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Preprint
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openaccess
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4.69 MB
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Adobe PDF
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CVPR17_poster_radhakrishna_achanta.pdf
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openaccess
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1.9 MB
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Adobe PDF
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