NDLI: Accurate visual word construction using a supervised approach

Content Provider	IEEE Xplore Digital Library
Author	Fernando, B. Fromont, E. Muselet, D. Sebban, M.
Copyright Year	2010
Description	Author affiliation: CIMET, University Jean Monnet, F-42023, Saint Etienne France (Fernando, B.) \|\| Université de Lyon, F-42023, Saint-Etienne, France (Fromont, E.; Muselet, D.; Sebban, M.)
Abstract	Most of the bag of visual words models are used to resorting to clustering techniques such as the K-means algorithm, to construct visual dictionaries. In order to improve their efficiency in the context of multi-class image classification tasks, we present in this paper a new incremental weighted average and gradient descent-based clustering algorithm which optimizes the visual word detection by the use of the class label of training examples. We show that this new supervised vector quantization allows us to better reveal concept or category-specific local feature distributions over the feature space. A large comparison with the standard K-means algorithm on the PASCAL VOC-2007 dataset is carried out. The results show that our visual word construction technique is much more suitable for learning efficient classifiers with Support Vector Machine and Random Forest algorithms.
Starting Page	1
Ending Page	7
File Size	270201
Page Count	7
File Format	PDF
ISBN	9781424496297
ISSN	21512205
e-ISBN	9781424496310
DOI	10.1109/IVCNZ.2010.6148844
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-08
Publisher Place	New Zealand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Visualization Dictionaries bag of visual words Vector quantization Clustering algorithms Feature extraction Vectors clustering supervised vector quantization
Content Type	Text
Resource Type	Article

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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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