Survey on Sparse Coded Features for Content Based Face Image Retrieval

International Journal of ComputerTrends and Technology (IJCTT)          
© 2014 by IJCTT Journal
Volume-8 Number-1                          
Year of Publication : 2014
Authors : D. JohnVictor , G. Selvavinayagam
DOI :  10.14445/22312803/IJCTT-V8P106


D. JohnVictor , G. Selvavinayagam. "Survey on Sparse Coded Features for Content Based Face Image Retrieval". International Journal of Computer Trends and Technology (IJCTT) 8(1):30-33, February 2014. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Content based image retrieval, a technique which uses visual contents of image to search images from large scale image databases according to users` interests. This paper provides a comprehensive survey on recent technology used in the area of content based face image retrieval. Nowadays digital devices and photo sharing sites are getting more popularity, large human face photos are available in database. Multiple types of facial features are used to represent discriminality on large scale human facial image database. Searching and mining of facial images are challenging problems and important research issues. Sparse representation on features provides significant improvement in indexing related images to query image.

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Content based image retrieval, sparse, face image, identity, facial attributes.