NDLI: Depth incorporating with color improves salient object detection

Content Provider	Springer Nature Link
Author	Tang, Yanlong Tong, Ruofeng Tang, Min Zhang, Yun
Copyright Year	2015
Abstract	Detecting salient objects in challenging images attracts increasing attention as many applications require more robust method to deal with complex images from the Internet. Prior methods produce poor saliency maps in challenging cases mainly due to the complex patterns in the background and internal color edges in the foreground. The former problem may introduce noises into saliency maps and the later forms the difficulty in determining object boundaries. Observing that depth map can supply layering information and more reliable boundary, we improve salient object detection by integrating two features: color information and depth information which are calculated from stereo images. The two features collaborate in a two-stage framework. In the object location stage, depth mainly helps to produce a noise-filtered salient patch, which indicates the location of the object. In the object boundary inference stage, boundary information is encoded in a graph using both depth and color information, and then we employ the random walk to infer more reliable boundaries and obtain the final saliency map. We also build a data set containing 100+ stereo pairs to test the effectiveness of our method. Experiments show that our depth-plus-color based method significantly improves salient object detection compared with previous color-based methods.
Starting Page	111
Ending Page	121
Page Count	11
File Format	PDF
ISSN	01782789
Journal	The Visual Computer
Volume Number	32
Issue Number	1
e-ISSN	14322315
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-01-20
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Salient object detection Depth information Color information Stereo images Computer Graphics Computer Science Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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