NDLI: Bundling centre for landmark image discovery

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Bundling centre for landmark image discovery

Content Provider	Springer Nature Link
Author	Zhang, Qian Qiu, Guoping
Copyright Year	2015
Abstract	This paper introduces a novel method to efficiently discover landmark images in large image collections. Each cluster is considered a combination of several sub-clusters, which are composed of images taken from different viewpoints of an identical landmark. For each sub-cluster, we find its local centre represented by a group of similar images and define it as the bundling centre (BC). Therefore, we start image discovery by identifying the BCs and accomplish the task by efficiently growing and merging those sub-clusters represented by different BCs. In our proposed method, we use a min-Hash-based method to build a sparse graph to avoid time-consuming, full-scale, exhaustive pairwise image matching. Based on the information provided by the sparse graph, BCs are identified as local dense neighbours sharing high intra-similarity. We have also proposed a weighted voting method to grow these BCs with high accuracy. More importantly, the fixed local centres ensure that each sub-cluster contains identical landmarks and generates results with high precision. In addition, compared to a single representative (iconic) image, the group of similar images obtained by each BC can provide more comprehensive cluster information and, thus, overcome the problem of low recall caused by information lost during visual word quantisation. We present the experimental results of three datasets and show that, without query expansion, our method can boost the landmark image discovery performances of current techniques.
Starting Page	35
Ending Page	50
Page Count	16
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	5
Issue Number	1
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2015-12-01
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Min-hash Sparse matching graph Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Information Systems Applications (incl. Internet) Multimedia Information Systems Landmark image discovery
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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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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