NDLI: A Pyramid Nearest Neighbor Search Kernel for object categorization

Content Provider	IEEE Xplore Digital Library
Author	Hong Cheng Rongchao Yu Zicheng Liu Yiguang Liu
Copyright Year	2012
Description	Author affiliation: University of Electronic Science and Technology of China, China (Hong Cheng; Rongchao Yu) \|\| Sichuan University, China (Yiguang Liu) \|\| Microsoft Research, Redmond, USA (Zicheng Liu)
Abstract	Nearest-Neighbor based Image Classification (N-NIC) has drawn considerable attention in the past several years because it does not require classifier training. Similar to an orderless Bag-of-Feature image representation, the traditional NNIC ignores global geometric correspondence. In this paper, we present a technique to exploit the global geometric correspondence in a nearest neighbor classifier framework. We divide an image into increasingly fine sub-regions like the Spatial Pyramid Matching (SPM) approach, and introduce a Pyramid Nearest Neighbor Search kernel by measuring the search similarity between a local descriptor and a feature set in each pyramid window. Instead of using a fixed weighting as in SPM, the weights of the pyramid windows are learned in a class-dependent manner. By doing so, we learn a class-specific geometric correspondence. Finally, an optimal nearest neighbor classifier framework is developed to incorporate the kernel functions over different pyramid windows. We evaluate our proposed approach on a number of public datasets, and show the results significantly outperform existing techniques.
Starting Page	2809
Ending Page	2812
File Size	645619
Page Count	4
File Format	PDF
ISBN	9781467322164
ISSN	10514651
e-ISBN	9784990644109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-11
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	ICPR Org Committee
Subject Keyword	Kernel Nearest neighbor searches Training Accuracy Educational institutions Testing Vectors
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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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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