Convexity constrained efficient superpixel and supervoxel extraction

Date

2015-04-01

Author

Tasli, H. Emrah
Çiğla, Cevahir
Alatan, Abdullah Aydın

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper presents an efficient superpixel (SP) and supervoxel (SV) extraction method that aims improvements over the state-of-the-art in terms of both accuracy and computational complexity. Segmentation performance is improved through convexity constrained distance utilization, whereas computational efficiency is achieved by replacing complete region processing by a boundary adaptation technique. Starting from the uniformly distributed, rectangular (cubical) equal size (volume) superpixels (supervoxels), region boundaries are iteratively adapted towards object edges. Adaptation is performed by assigning the boundary pixels to the most similar neighboring SPs (SVs). At each iteration, SP (SV) regions are updated; hence, progressively converging to compact pixel groups. Detailed experimental comparisons against the state-of-the-art competing methods validate the performance of the proposed technique considering both accuracy and speed.

Subject Keywords

Superpixel, Segmentation, Geometry constrain, Supervoxel

URI

https://hdl.handle.net/11511/48983

Journal

SIGNAL PROCESSING-IMAGE COMMUNICATION

DOI

https://doi.org/10.1016/j.image.2015.02.005

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

H. E. Tasli, C. Çiğla, and A. A. Alatan, “Convexity constrained efficient superpixel and supervoxel extraction,” SIGNAL PROCESSING-IMAGE COMMUNICATION, pp. 71–85, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48983.