View-Consistent 4D Light Field Superpixel Segmentation
Numair Khan, Qian Zhang, Lucas Kasser, Henry Stone, Min H. Kim, James Tompkin
Abstract
Many 4D light field processing applications rely on superpixel segmentations, for which occlusion-aware view consistency is important. Yet, existing methods often enforce consistency by propagating clusters from a central view only, which can lead to inconsistent superpixels for non-central views. Our proposed approach combines an occlusion-aware angular segmentation in horizontal and vertical EPI spaces with an occlusion-aware clustering and propagation step across all views. Qualitative video demonstrations show that this helps to remove flickering and inconsistent boundary shapes versus the state-of-the-art approach, and quantitative metrics reflect these findings with improved boundary accuracy and view consistency scores.
BibTeX
@inproceedings{iccv2019_viewconsistent4d,
title = {View-Consistent 4D Light Field Superpixel Segmentation},
author = {Numair Khan and Qian Zhang and Lucas Kasser and Henry Stone and Min H. Kim and James Tompkin},
booktitle = {ICCV 2019},
year = {2019}
}