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Authors: Gangbiao Chen and Chun Yuan

Affiliation: Tsinghua University, China

ISBN: 978-989-758-089-5

Keyword(s): Saliency Detection, Sparse Coding, Depth Information, Centre Shift, Human Visual Acuity.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Visual Attention and Image Saliency

Abstract: In this paper, we modified the region-based Human Visual System (HVS) model by import two features, sparse feature and depth feature. The input image is firstly divided into small regions. Then the contrast, sparse and depth feature of each region are extracted. We calculate the center-surround feature differences for saliency detection. In this step, the center shift method is adopted. In the weighting step, the human visual acuity is adopted. Compared with the existing related algorithms, experimental results on a large public database show that the modified method works better and can obtain a more accurate result.

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Paper citation in several formats:
Chen, G. and Yuan, C. (2015). Saliency Detection based on Depth and Sparse Features.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 441-446. DOI: 10.5220/0005292604410446

@conference{visapp15,
author={Gangbiao Chen. and Chun Yuan.},
title={Saliency Detection based on Depth and Sparse Features},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={441-446},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005292604410446},
isbn={978-989-758-089-5},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Saliency Detection based on Depth and Sparse Features
SN - 978-989-758-089-5
AU - Chen, G.
AU - Yuan, C.
PY - 2015
SP - 441
EP - 446
DO - 10.5220/0005292604410446

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