Improving View-consistency on 4D Light Field Superpixel Segmentation

라이트필드 영상 슈퍼픽셀 분할의 시점간 일관성 개선

  • Yim, Jonghoon (Department of Electrical and Computer Engineering Sungkyunkwan University) ;
  • Duong, Vinh Van (Department of Electrical and Computer Engineering Sungkyunkwan University) ;
  • Huu, Thuc Ngyuen (Department of Electrical and Computer Engineering Sungkyunkwan University) ;
  • Jeon, Byeungwoo (Department of Electrical and Computer Engineering Sungkyunkwan University)
  • 임종훈 (성균관대학교 전자전기컴퓨터공학과) ;
  • ;
  • ;
  • 전병우 (성균관대학교 전자전기컴퓨터공학과)
  • Published : 2021.06.23

Abstract

Light field (LF) superpixel segmentation aims to group the similar pixels not only in the single image but also in the other views to improve the computational efficiency of further applications like object detection and pattern recognition. Among the state-of-the-art methods, there is an approach to segment the LF images while enforcing the view consistency. However, it leaves too much noise and inaccuracy in the shape of superpixels. In this paper, we modify the process of the clustering step. Experimental results demonstrate that our proposed method outperforms the existing method in terms of view-consistency.

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Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2020R1A2C2007673)