DocumentCode :
253416
Title :
Measuring visual vocabulary appropriateness by dispersion index and its improvement by globalizing SIFT descriptors
Author :
Suzuki, Izumi
Author_Institution :
Dept. of Manage. & Inf. Syst. Eng., Nagaoka Univ. of Technol., Nagaoka, Japan
fYear :
2014
fDate :
19-21 Nov. 2014
Firstpage :
179
Lastpage :
184
Abstract :
Correct classification rates are often used to measure the appropriateness of a visual-word vocabulary. Appropriateness is also measured by the dispersion index, a technique in quantitative ecology that estimates the distribution pattern of individuals. In the bag-of-keypoints method of making a visual vocabulary, the size of the vocabulary is examined. In addition, a method to globalize a local feature is proposed. In this globalization method, each descriptor is modified to be similar to adjacent descriptors and therefore provides more opportunity for a visual word to form clumps on a test image. Although applying the index is limited by the classifier, we found that appropriateness is measured by estimating the average dispersion index for every visual word. In addition, this paper discusses another method for creating a visual-word vocabulary that is more appropriate for classification by globalization.
Keywords :
feature extraction; image classification; learning (artificial intelligence); SIFT descriptors; bag-of-keypoints method; classification rates; dispersion index; feature classification; feature globalization; quantitative ecology; scale invariant feature transforms; visual vocabulary appropriateness measurement; visual-word vocabulary; vocabulary size; Dispersion; Feature extraction; Globalization; Indexes; Support vector machines; Visualization; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2014 IEEE 15th International Symposium on
Conference_Location :
Budapest
Type :
conf
DOI :
10.1109/CINTI.2014.7028672
Filename :
7028672
Link To Document :
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