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BASS: Boundary-aware superpixel segmentation

AuthorsRubio Romano, Antonio ; Yu, LongLong; Simo-Serra, Edgar ; Moreno-Noguer, Francesc
Issue Date2016
PublisherInstitute of Electrical and Electronics Engineers
Citation23rd International Conference on Pattern Recognition (ICPR): 2824-2829 (2016)
AbstractWe propose a new superpixel algorithm based on exploiting the boundary information of an image, as objects in images can generally be described by their boundaries. Our proposed approach initially estimates the boundaries and uses them to place superpixel seeds in the areas in which they are more dense. Afterwards, we minimize an energy function in order to expand the seeds into full superpixels. In addition to standard terms such as color consistency and compactness, we propose using the geodesic distance which concentrates small superpixels in regions of the image with more information, while letting larger superpixels cover more homogeneous regions. By both improving the initialization using the boundaries and coherency of the superpixels with geodesic distances, we are able to maintain the coherency of the image structure with fewer superpixels than other approaches. We show the resulting algorithm to yield smaller Variation of Information metrics in seven different datasets while maintaining Undersegmentation Error values similar to the state-of-the-art methods.
DescriptionTrabajo presentado a la 23rd International Conference on Pattern Recognition, celebrada en Cancún (México) del 5 al 8 de diciembre de 2016.
Publisher version (URL)https://doi.org/10.1109/ICPR.2016.7900064
Identifiersdoi: 10.1109/ICPR.2016.7900064
isbn: 978-1-5090-4847-2
Appears in Collections:(IRII) Libros y partes de libros
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