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Histogram of visual words based on locally adaptive regression kernels descriptors for image feature extraction

Qian, Jianjun and Yang, Jian and Zhang, Nan and Yang, Zhangjing (2014) Histogram of visual words based on locally adaptive regression kernels descriptors for image feature extraction. Neurocomputing, 129 . pp. 516-527. ISSN 0925-2312. https://resolver.caltech.edu/CaltechAUTHORS:20140404-134734320

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Abstract

Image feature extraction is one of the most important problems for image recognition system. We tackle this by combing the locally adaptive regression kernel descriptors (LARK), bag-of-visual-words and sparse representation. Specifically, this paper makes two main contributions: (1) we introduce a novel method called histogram of visual words based on locally adaptive regression kernels descriptors (HWLD) for image feature extraction. LARK is used to describe the image local information and build the visual vocabulary. Each pixel of an image is assigned to the visual words and gets the corresponding weights. Image feature vector is obtained by subdividing the image and computing the accumulative weight histograms of visual words in these sub-blocks. (2) The K nearest neighbor based sparse representation (KNN-SR) is presented for assigning the visual words. Compared with nearest neighbors based method, KNN-SR has stronger discriminant power to identify different patches in the image. Experimental results on the AR face image set, the CMU-PIE face image set, the ETH80 object image set and the Nister image set demonstrate that our method is more effective than some state-of-the-art feature extraction methods.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1016/j.neucom.2013.09.007DOIArticle
http://www.sciencedirect.com/science/article/pii/S0925231213009107PublisherArticle
Additional Information:© 2013 Elsevier B.V. Received 29 August 2012. Received in revised form 24 June 2013. Accepted 3 September 2013. Communicated by Xiaofei He. Available online 19 October 2013. The authors would like to thank the editor and the anonymous reviewers for their critical and constructive comments and suggestions. This work was partially supported by the National Science Fund for Distinguished Young Scholars under Grant Nos. 61125305, 61233011 and 61203243, the Key Project of Chinese Ministry of Education under Grant No. 313030.
Funders:
Funding AgencyGrant Number
NSF for Distinguished Young Scholars61125305
NSF for Distinguished Young Scholars61233011
NSF for Distinguished Young Scholars61203243
Chinese Ministry of Education Key Project313030
Subject Keywords:Locally adaptive regression kernels descriptors; Bag-of-visual-words; Feature extraction; Sparse representation
Record Number:CaltechAUTHORS:20140404-134734320
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140404-134734320
Official Citation:Jianjun Qian, Jian Yang, Nan Zhang, Zhangjing Yang, Histogram of visual words based on locally adaptive regression kernels descriptors for image feature extraction, Neurocomputing, Volume 129, 10 April 2014, Pages 516-527, ISSN 0925-2312, http://dx.doi.org/10.1016/j.neucom.2013.09.007. (http://www.sciencedirect.com/science/article/pii/S0925231213009107)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:44666
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:04 Apr 2014 21:38
Last Modified:03 Oct 2019 06:20

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