Abstract
For superpixel segmentation, simple linear iterative clustering (SLIC) has attracted much attention due to its outstanding performance in terms of speed and accuracy. However, computational-efficiency challenge still remains for applying it to real-time applications. In this paper, by applying the Cauchy-Schwarz inequality, we derive a simple condition to get rid of unnecessary operations from the cluster inspection procedure. Candidate clusters can be early eliminated without cluster inspection requiring high computation. In the experimental results, it is confirmed that the proposed superpixel segmentation algorithm improves efficiency of SLIC by 21 % on average without any degradation in segmentation performance.
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Choi, KS., Oh, KW. (2015). Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_65
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DOI: https://doi.org/10.1007/978-3-319-19390-8_65
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