DocumentCode :
130919
Title :
Quick search algorithms based on ethnic facial image database
Author :
BaoWei Hou ; Rui Zheng ; GuoSheng Yang
Author_Institution :
Dept. of Inf. Eng., Minzu Univ. of China, Beijing, China
fYear :
2014
fDate :
27-29 June 2014
Firstpage :
573
Lastpage :
576
Abstract :
The current popular image features index structure can be divided into tree-based structures, hash-based structures and machine learning based structures. In face recognition, selecting the appropriate image feature indexing structure to achieve large-scale face image matching has aways been a problem. In this paper, we present a global image features indexing method based on complete binary tree, using the ethnic facial image database, by contrast with the local sensitive hash(LSH), and principal component analysis (PCA) is adopted to extract facial image features for convienent. Experimental results show that the proposed method is superior to the local sensitive hashing in velocity.
Keywords :
database indexing; face recognition; feature extraction; image matching; learning (artificial intelligence); principal component analysis; tree data structures; visual databases; LSH; PCA; complete binary tree; ethnic facial image database; face recognition; facial image feature extraction; global image feature indexing method; hash-based structures; image feature indexing structure; large-scale face image matching; local sensitive hash; machine learning based structures; principal component analysis; tree-based structures; Binary trees; Face; Feature extraction; Indexing; Principal component analysis; Vectors; Vegetation; LSH; PCA; complete binary tree; global features;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4799-3278-8
Type :
conf
DOI :
10.1109/ICSESS.2014.6933633
Filename :
6933633
Link To Document :
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