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Conference Paper Plenoptic Image Segmentation with Region-based Graph Cut Approach
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Authors
Seongjin Park, DoHyung Kim, Seong-Jun Bae, Jae Woo Kim, Ho Wook Jang
Issue Date
2017-10
Citation
Global Conference on Consumer Electronics (GCCE) 2017, pp.1-2
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/GCCE.2017.8229376
Project Code
17HS1100, Authoring Platform Technology for Next-Generation Plen-Optic Contents, Kim Do Hyung
Abstract
Plenoptic images captured from plenoptic cameras provide angular information as well as conventional spatial information of the scene. Using the angular information, plenoptic imaging can generate multiview images. In this paper, we developed approaches for object segmentation on 4D hyper volume represented with the multiview images. Our approaches are based on graph cut algorithms and applied connected component labeling to divide pre-segmented regions to reduce computation time. The region-based graph cut segmentation is composed of region graph creation, weight computation, and graph cut optimization on the pre-segmented regions. The experiments demonstrated that the proposed method produced more accurate results comparing to the results from conventional graph cut methods.
KSP Keywords
Angular information, Connected Component Labeling, Graph cut segmentation, Object segmentation, Plenoptic Imaging, Plenoptic camera, Plenoptic image, Region Graph, Region-based, computation time, image segmentation