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M. Van den Bergh, X. Boix, G. Roig, B. de Capitani, L. van Gool. SEEDS – Superpixels Extracted via Energy-Driven Sampling. European Conference on Computer Vision, pages 13- 26, 2012.

Van den Bergh et al. propose a superpixel algorithm called SEEDS using color histograms to refine an initial superpixel segmentation. The main goal of my bachelor thesis is the integration of depth information into SEEDS, see my bachelor thesis proposal and the slides of my introductory talk. Figure 1 shows images from the validation set of the Berkeley Segmentation Dataset [1] oversegmented using the original implementation of SEEDS.

Update. Thorough evaluation of both the original implementation and my implementation of SEEDS can be found in my bachelor thesis: Bachelor Thesis “Superpixel Segmentation Using Depth Information”.

bsd_1_seeds bsd_2_seeds bsd_3_seeds bsd_4_seeds bsd_5_seeds

Figure 1: Superpixel segmentations with approximately $600$ superpixels generated by the original implementation of SEEDS.
  • [1] P. Arbeláez, M. Maire, C. Fowlkes, J. Malik. Contour detection and hierarchical image segmentation. Transactions on Pattern Analysis and Machine Intelligence, volume 33, number 5, pages 898–916, 2011.

What is your opinion on the summarized work? Or do you know related work that is of interest? Let me know your thoughts in the comments below: