research-article

Visual saliency based bag of phrases for image retrival

Authors:

Lijuan Duan,

Wei Ma,

Jun Miao,

Xuan ZhangAuthors Info & Claims

VRCAI '14: Proceedings of the 13th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry

Pages 243 - 246

https://doi.org/10.1145/2670473.2670510

Published: 30 November 2014 Publication History

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Abstract

This paper presents a saliency based bag-of-phrases (Saliency-BoP for short) method for image retrieval. It combines saliency detection with visual phrase construction to extract bag-of-phrase features. To achieve this, the method first detects salient regions in images. Then, it constructs visual phrases using the word pairs which are from the same salient regions. Finally, it extracts the bag of visual phrases from the first K salient regions to describe images. Experimental results on Corel 1K and Microsoft Research Cambridge image database demonstrated that the Saliency-BoP method outperforms related methods such as Bag-of-Words (BoW) or Saliency-BoW.

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Cited By

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Wei SLiao LLi JZheng QYang FZhao Y(2019)Saliency Inside: Learning Attentive CNNs for Content-Based Image RetrievalIEEE Transactions on Image Processing10.1109/TIP.2019.291351328:9(4580-4593)Online publication date: Sep-2019
https://doi.org/10.1109/TIP.2019.2913513
Zheng QWei SLi JYang FZhao Y(2017)Uncovering the Effect of Visual Saliency on Image RetrievalComputer Vision10.1007/978-981-10-7302-1_15(170-179)Online publication date: 30-Nov-2017
https://doi.org/10.1007/978-981-10-7302-1_15

Index Terms

Visual saliency based bag of phrases for image retrival
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations

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Published In

VRCAI '14: Proceedings of the 13th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry

November 2014

246 pages

ISBN:9781450332545

DOI:10.1145/2670473

General Chairs:
Xiaogang Jin
Zhejiang University, China
,
Nadia Magnenat-Thalmann
Nanyang Technological University, Singapore and MIRALab, University of Geneva, Switzerland
,
Hyun Seung Yang
Korea Advanced Institute of Science & Technology, Korea
,
Program Chairs:
Xubo Yang
Shanghai Jiao Tong University, China
,
Tomasz Bednarz
CSRIO, Australia
,
Issei Fujishiro
Keio University, Japan

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 November 2014

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Funding Sources

NTFYPSTS
Ministry of Science and Technology of the People's Republic of China
Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions
National Natural Science Foundation of China
Beijing University of Technology

Conference

VRCAI 2014

Sponsor:

SIGGRAPH

VRCAI 2014: 13th ACM International Conference on Virtual Reality Continuum and Its Applications in Industry

November 30 - December 2, 2014

Shenzhen, China

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Overall Acceptance Rate 51 of 107 submissions, 48%

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Cited By

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Wei SLiao LLi JZheng QYang FZhao Y(2019)Saliency Inside: Learning Attentive CNNs for Content-Based Image RetrievalIEEE Transactions on Image Processing10.1109/TIP.2019.291351328:9(4580-4593)Online publication date: Sep-2019
https://doi.org/10.1109/TIP.2019.2913513
Zheng QWei SLi JYang FZhao Y(2017)Uncovering the Effect of Visual Saliency on Image RetrievalComputer Vision10.1007/978-981-10-7302-1_15(170-179)Online publication date: 30-Nov-2017
https://doi.org/10.1007/978-981-10-7302-1_15

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