NDLI: A Novel Scene Descriptor and Outdoor Scene Recognition Method

Content Provider	IEEE Xplore Digital Library
Author	Jun Chu Yongyi Zhang Guihua Zhao Lu Wang
Copyright Year	2015
Description	Author affiliation: Inst. of Comput. Vision, Nanchang Hangkong Univ., Nanchang, China (Jun Chu; Yongyi Zhang; Guihua Zhao; Lu Wang)
Abstract	Bag-of-Words representation based on visual words has been approved to be used widely in scene classification. Visual words are usually constructed by using SIFT(Scale Invariant Feature Transform) of patches. Traditional SIFT descriptor is limited in describe the outdoor scene completely and accurately because it does not consider the multi-directional context and global color information of image. In this paper, we propose that a new scene descriptor and classification method based on SIFT(NC-SIFT, Color Multi-Directional Context SIFT) feature descriptor of key word of patches. Firstly, local SIFT combined with the context information is extracted based on image patch, Then, BOW(Bag of Words) is obtained by K-means clustering and histogram statistics and the scene recognition based on SVM classifier using BOW which fuse the global color vector is accomplished respectively.
Starting Page	374
Ending Page	381
File Size	298489
Page Count	8
File Format	PDF
e-ISBN	9781467393232
DOI	10.1109/ISKE.2015.33
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-24
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Vocabulary Histograms Image recognition Image color analysis Buildings support vector machine (SVM) context information Feature extraction scene recognition bag of words(BOW)
Content Type	Text
Resource Type	Article

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