Image Guided Cost Aggregation for Hierarchical Depth Map Fusion

Thilo Borgmann, Thomas Sikora

2013

Abstract

Estimating depth from a video sequence is still a challenging task in computer vision with numerous applications. Like other authors we utilize two major concepts developed in this field to achieve that task which are the hierarchical estimation of depth within an image pyramid as well as the fusion of depth maps from different views. We compare the application of various local matching methods within such a combined approach and can show the relative performance of local image guided methods in contrast to commonly used fixed–window aggregation. Since efficient implementations of these image guided methods exist and the available hardware is rapidly enhanced, the disadvantage of their more complex but also parallel computation vanishes and they will become feasible for more applications.

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Paper Citation


in Harvard Style

Borgmann T. and Sikora T. (2013). Image Guided Cost Aggregation for Hierarchical Depth Map Fusion . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 199-207. DOI: 10.5220/0004212901990207


in Bibtex Style

@conference{visapp13,
author={Thilo Borgmann and Thomas Sikora},
title={Image Guided Cost Aggregation for Hierarchical Depth Map Fusion},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={199-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004212901990207},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Image Guided Cost Aggregation for Hierarchical Depth Map Fusion
SN - 978-989-8565-48-8
AU - Borgmann T.
AU - Sikora T.
PY - 2013
SP - 199
EP - 207
DO - 10.5220/0004212901990207