Abstract
Using superpixels instead of pixels has become a popular pre-processing step in computer vision. Currently, about fifteen oversegmentation methods have been proposed. The last evaluation, realized by Stutz et al. in 2015, concludes that the five more competitive algorithms achieve similar results. By introducing HSID, a new dataset, we point out unexpected difficulties encountered by state-of-the-art oversegmentation methods.
The work of Bérengère Mathieu was partially supported by ANR-11-LABX-0040-CIMI within the program ANR-11-IDEX-0002-02.
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Mathieu, B., Crouzil, A., Puel, J.B. (2017). Oversegmentation Methods: A New Evaluation. In: Alexandre, L., Salvador Sánchez, J., Rodrigues, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2017. Lecture Notes in Computer Science(), vol 10255. Springer, Cham. https://doi.org/10.1007/978-3-319-58838-4_21
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