loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Tran Phuong Nhung 1 ; Cam-Tu Nguyen 2 ; Jinhee Chun 1 ; Ha Vu Le 3 and Takeshi Tokuyama 1

Affiliations: 1 Tohoku University, Japan ; 2 Nanjing University, China ; 3 VNU University of Engineering and Technology, Vietnam

ISBN: 978-989-8565-75-4

Keyword(s): Visual Saliency, Image Annotation, Multiple Instance Learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Data Reduction and Quality Assessment ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Mining High-Dimensional Data ; Mining Multimedia Data ; Soft Computing ; Symbolic Systems ; Visual Data Mining and Data Visualization

Abstract: This paper presents a novel approach to image annotation based on multi-instance learning (MIL) and saliency map. Image Annotation is an automatic process of assigning labels to images so as to obtain semantic retrieval of images. This problem is often ambiguous as a label is given to the whole image while it may only corresponds to a small region in the image. As a result, MIL methods are suitable solutions to resolve the ambiguities during learning. On the other hand, saliency detection aims at detecting foreground/background regions in images. Once we obtain this information, labels and image regions can be aligned better, i.e., foreground labels (background labels) are more sensitive to foreground areas (background areas). Our proposed method, which is based on an ensemble of MIL classifiers from two views (background/foreground), improves annotation performance in comparison to baseline methods that do not exploit saliency information.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 107.23.37.199

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Phuong Nhung, T.; Phuong Nhung, T.; Nguyen, C.; Chun, J.; Le, H. and Tokuyama, T. (2013). A Multiple Instance Learning Approach to Image Annotation with Saliency Map.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 152-159. DOI: 10.5220/0004543901520159

@conference{kdir13,
author={Tran Phuong Nhung. and Tran Phuong Nhung. and Cam{-}Tu Nguyen. and Jinhee Chun. and Ha Vu Le. and Takeshi Tokuyama.},
title={A Multiple Instance Learning Approach to Image Annotation with Saliency Map},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={152-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004543901520159},
isbn={978-989-8565-75-4},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - A Multiple Instance Learning Approach to Image Annotation with Saliency Map
SN - 978-989-8565-75-4
AU - Phuong Nhung, T.
AU - Phuong Nhung, T.
AU - Nguyen, C.
AU - Chun, J.
AU - Le, H.
AU - Tokuyama, T.
PY - 2013
SP - 152
EP - 159
DO - 10.5220/0004543901520159

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.