Evaluation of Deep Image Descriptors for Texture Retrieval

Bojana Gajic, Eduard Vazquez, Ramon Baldrich

Abstract

The increasing complexity learnt in the layers of a Convolutional Neural Network has proven to be of great help for the task of classification. The topic has received great attention in recently published literature. Nonetheless, just a handful of works study low-level representations, commonly associated with lower layers. In this paper, we explore recent findings which conclude, counterintuitively, the last layer of the VGG convolutional network is the best to describe a low-level property such as texture. To shed some light on this issue, we are proposing a psychophysical experiment to evaluate the adequacy of different layers of the VGG network for texture retrieval. Results obtained suggest that, whereas the last convolutional layer is a good choice for a specific task of classification, it might not be the best choice as a texture descriptor, showing a very poor performance on texture retrieval. Intermediate layers show the best performance, showing a good combination of basic filters, as in the primary visual cortex, and also a degree of higher level information to describe more complex textures.

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Paper Citation


in Harvard Style

Gajic B., Vazquez E. and Baldrich R. (2017). Evaluation of Deep Image Descriptors for Texture Retrieval . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-226-4, pages 251-257. DOI: 10.5220/0006129302510257


in Bibtex Style

@conference{visapp17,
author={Bojana Gajic and Eduard Vazquez and Ramon Baldrich},
title={Evaluation of Deep Image Descriptors for Texture Retrieval},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={251-257},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006129302510257},
isbn={978-989-758-226-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)
TI - Evaluation of Deep Image Descriptors for Texture Retrieval
SN - 978-989-758-226-4
AU - Gajic B.
AU - Vazquez E.
AU - Baldrich R.
PY - 2017
SP - 251
EP - 257
DO - 10.5220/0006129302510257