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Detecting Non-lambertian Materials in Video

Topics: Color and Texture Analyses; Features Extraction; Human and Computer Interaction; Image Formation, Acquisition Devices and Sensors; Image Generation Pipeline: Algorithms and Techniques; Object Detection and Localization; Shape Representation and Matching; Video Surveillance and Event Detection

Authors: Seyed Mahdi Javadi ; Yongmin Li and Xiaohui Liu

Affiliation: Brunel University, United Kingdom

Keyword(s): Texture Analysis, Object Recognition, Lambert Model, Shiny Surface, Matt Texture, Glass and Water Detection.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Features Extraction ; Human and Computer Interaction ; Human-Computer Interaction ; Image and Video Analysis ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Image Generation Pipeline: Algorithms and Techniques ; Motion, Tracking and Stereo Vision ; Shape Representation and Matching ; Video Surveillance and Event Detection

Abstract: This paper describes a novel method to identify and distinguish shiny and glossy materials in videos automatically. The proposed solution works by analyzing the logarithm of chromaticity of sample pixels from various materials over a period of time to differentiate between shiny and matt textures. The Lambertian materials have different reflectance model and the distribution of their chromaticity is not the same as non-Lambertian texture. We will use this to detect shiny materials. This system has many application in texture and object recognition, water leakage and oil spillage detection systems.

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Paper citation in several formats:
Javadi, S.; Li, Y. and Liu, X. (2017). Detecting Non-lambertian Materials in Video. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP; ISBN 978-989-758-225-7; ISSN 2184-4321, SciTePress, pages 254-259. DOI: 10.5220/0006185002540259

@conference{visapp17,
author={Seyed Mahdi Javadi. and Yongmin Li. and Xiaohui Liu.},
title={Detecting Non-lambertian Materials in Video},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP},
year={2017},
pages={254-259},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006185002540259},
isbn={978-989-758-225-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP
TI - Detecting Non-lambertian Materials in Video
SN - 978-989-758-225-7
IS - 2184-4321
AU - Javadi, S.
AU - Li, Y.
AU - Liu, X.
PY - 2017
SP - 254
EP - 259
DO - 10.5220/0006185002540259
PB - SciTePress