NDLI: Bregman pooling: feature-space local pooling for image classification

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Bregman pooling: feature-space local pooling for image classification

Content Provider	Springer Nature Link
Author	Ogawa, Takahiro Najjar, Alameen Haseyama, Miki
Copyright Year	2015
Abstract	In this paper, we propose a novel feature-space local pooling method for the commonly adopted architecture of image classification. While existing methods partition the feature space based on visual appearance to obtain pooling bins, learning more accurate space partitioning that takes semantics into account boosts performance even for a smaller number of bins. To this end, we propose partitioning the feature space over clusters of visual prototypes common to semantically similar images (i.e., images belonging to the same category). The clusters are obtained by Bregman co-clustering applied offline on a subset of training data. Therefore, being aware of the semantic context of the input image, our features have higher discriminative power than do those pooled from appearance-based partitioning. Testing on four datasets (Caltech-101, Caltech-256, 15 Scenes, and 17 Flowers) belonging to three different classification tasks showed that the proposed method outperforms methods in previous works on local pooling in the feature space for less feature dimensionality. Moreover, when implemented within a spatial pyramid, our method achieves comparable results on three of the datasets used.
Starting Page	247
Ending Page	259
Page Count	13
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	4
Issue Number	4
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2015-09-04
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bregman divergence Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Image representation Feature pooling Information Systems Applications (incl. Internet) Multimedia Information Systems Co-clustering Image classification
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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