research-article

Depth Information Fused Salient Object Detection

Authors:

Zehai SongAuthors Info & Claims

ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and Service

Pages 66 - 70

https://doi.org/10.1145/2632856.2632938

Published: 10 July 2014 Publication History

Abstract

Saliency Detection has emerged as a hot topic due to its potential application in image and video understanding. Most existing saliency detection algorithms focus on two-dimensional information while the depth information is often ignored. In this paper, we first create the salient object ground truth of a specific image dataset which contains 600 RGB-D (color and depth information) images taken from different surroundings with different angle and intensity of illumination. The depth image describes the depth information of each object in the image from the perspective of a viewer, and the intensity value of every pixel in the depth image denotes the depth information. With the help of depth information, a more precise object description can be acquired. Furthermore, several state-of-the-art saliency detection models can be utilized to generate 2D salient maps, which can be fused with the depth map to detect the salient object in a given image. Experimental results demonstrate the effectiveness of the proposed method.

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Cited By

Li ZLang CFeng SWang T(2018)Saliency ranker: A new salient object detection methodJournal of Visual Communication and Image Representation10.1016/j.jvcir.2017.11.00450(16-26)Online publication date: Jan-2018
https://doi.org/10.1016/j.jvcir.2017.11.004
Feng DBarnes NYou SMcCarthy C(2016)Local Background Enclosure for RGB-D Salient Object Detection2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR.2016.257(2343-2350)Online publication date: Jun-2016
https://doi.org/10.1109/CVPR.2016.257
Guo JRen TBei JZhu YJain RJiang SSmith JSang JLi G(2015)Salient object detection in RGB-D image based on saliency fusion and propagationProceedings of the 7th International Conference on Internet Multimedia Computing and Service10.1145/2808492.2808551(1-5)Online publication date: 19-Aug-2015
https://dl.acm.org/doi/10.1145/2808492.2808551

Index Terms

Depth Information Fused Salient Object Detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding

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Published In

cover image ACM Other conferences

ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and Service

July 2014

430 pages

ISBN:9781450328104

DOI:10.1145/2632856

General Chairs:
Hanzi Wang
Xiamen University, China
,
Larry Davis
University of Maryland, USA
,
Program Chairs:
Wenwu Zhu
Tsinghua University, China
,
Stephan Kopf
University of Mannheim, Germany
,
Yanyun Qu
Xiamen University, China
,
Publications Chairs:
Jun Yu
Xiamen University, China
,
Jitao Sang
Institute of Automation, CAS, China
,
Tao Mei
Microsoft Research Asia, China

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

NSF of China: National Natural Science Foundation of China
Beijing ACM SIGMM Chapter

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 July 2014

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ICIMCS '14

ICIMCS '14: International Conference on Internet Multimedia Computing and Service

July 10 - 12, 2014

Xiamen, China

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Overall Acceptance Rate 163 of 456 submissions, 36%

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Cited By

Li ZLang CFeng SWang T(2018)Saliency ranker: A new salient object detection methodJournal of Visual Communication and Image Representation10.1016/j.jvcir.2017.11.00450(16-26)Online publication date: Jan-2018
https://doi.org/10.1016/j.jvcir.2017.11.004
Feng DBarnes NYou SMcCarthy C(2016)Local Background Enclosure for RGB-D Salient Object Detection2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR.2016.257(2343-2350)Online publication date: Jun-2016
https://doi.org/10.1109/CVPR.2016.257
Guo JRen TBei JZhu YJain RJiang SSmith JSang JLi G(2015)Salient object detection in RGB-D image based on saliency fusion and propagationProceedings of the 7th International Conference on Internet Multimedia Computing and Service10.1145/2808492.2808551(1-5)Online publication date: 19-Aug-2015
https://dl.acm.org/doi/10.1145/2808492.2808551

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