NDLI: Beyond local phase quantization: Mid-level blurred image representation using fisher vector

Content Provider	IEEE Xplore Digital Library
Author	Mengyu Zhu Zhiguo Cao Yang Xiao Xiaokang Xie
Copyright Year	2015
Description	Author affiliation: Sch. of Autom., Huazhong Univ. of Sci. & Technol., Wuhan, China (Mengyu Zhu; Zhiguo Cao; Yang Xiao; Xiaokang Xie)
Abstract	Blurred image recognition is still remaining as a challenging task, while with the wide applications. One principal way for solving this problem is to extract the blur-invariant visual descriptor. To this end, local phase quantization (LPQ) was ever proposed, and achieved promising results. In this paper, to further enhance LPQ's performance, we propose to apply Fisher Vector (FV) encoding approach to acquire the mid-level blurred image representation. To our knowledge, it is the first time that the descriptive power of FV for blurred image recognition has been investigated. Instead of being extracted holistically from the whole image as previously, LPQ is acquired in a densely sampled way. That is, a sliding sub-window will screen the image with certain vertical and horizontal strides. LPQs are then extracted from all the resulting sub-windows respectively. In addition, to maintain local spatial structure information, each sub-window will be divided into finer cells. After being FV encoded, the local LPQs are aggregated using sum-pooling to generate the image signature. The experimental results on three datasets demonstrate that FV can enhance LPQ's performance significantly, and our proposition also outperforms the other blur-invariant descriptors by large margins in most cases.
Starting Page	1890
Ending Page	1894
File Size	1061526
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351129
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image representation Image recognition Quantization (signal) Image coding Data mining Image restoration Face fisher vector Blurred image recognition local phase quantization
Content Type	Text
Resource Type	Article

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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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