Image Pre-Segmentation from Shadow Masks

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vmv20251239.pdf (32.59 MB)
Date
2025
Authors
Heep, Moritz
Parakkat, Amal Dev
Zell, Eduard
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Image segmentation has gained a lot of attention in the past. When working with photometric stereo data, we discovered that shadow cues provide valuable spatial information, especially when combining multiple images of the same scene under different lighting conditions. In the following, we present a robust method to pre-segment images, relying heavily on shadow masks as the main input. We first detect object contours from light to shadow transitions. In the second step, we run an image segmentation algorithm based on Delaunay triangulation that is capable of closing the gaps between contours. Our method requires spatial input data but is free from training data. Initial results look promising, generating pre-segmentations close to recent data-driven image segmentation algorithms.
Description

CCS Concepts: Computing methodologies → Image processing

        
@inproceedings{
10.2312:vmv.20251239
,
booktitle = {
Vision, Modeling, and Visualization
},
editor = {
Egger, Bernhard
 and 
Günther, Tobias
},
title = {{
Image Pre-Segmentation from Shadow Masks
}},
author = {
Heep, Moritz
 and 
Parakkat, Amal Dev
 and 
Zell, Eduard
},
year = {
2025
},
publisher = {
The Eurographics Association
},
ISBN = {
978-3-03868-294-3
},
DOI = {
10.2312/vmv.20251239
}
}
Citation
URI
https://doi.org/10.2312/vmv.20251239
 https://diglib.eg.org/handle/10.2312/vmv20251239
Collections
VMV2025