Convexity constrained efficient superpixel and supervoxel extraction

Tasli H. E., Çiğla C., Alatan A. A.

SIGNAL PROCESSING-IMAGE COMMUNICATION, vol.33, pp.71-85, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 33
  • Publication Date: 2015
  • Doi Number: 10.1016/j.image.2015.02.005
  • Journal Name: SIGNAL PROCESSING-IMAGE COMMUNICATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.71-85
  • Keywords: Superpixel, Segmentation, Geometry constrain, Supervoxel
  • Middle East Technical University Affiliated: Yes

Abstract

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. (C) 2015 Elsevier B.V. All rights reserved.