AESC Technique For Scalable Face Image Retrieval

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-22 Number-2
Year of Publication : 2015
Authors : Priyanka Shinkar, Rekha Ghayal, Pradnya Ingale, Parin Gaikwad
  10.14445/22312803/IJCTT-V22P117

MLA

Priyanka Shinkar, Rekha Ghayal, Pradnya Ingale, Parin Gaikwad "AESC Technique For Scalable Face Image Retrieval". International Journal of Computer Trends and Technology (IJCTT) V22(2):86-90, April 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Now a day’s photos with people are major interest of users. Thus, large scale content-based face image retrieval is an enabling technology. In this work, we aim to utilize automatically detected human face attributes that contains semantic cues of the face photos, it improve content based face retrieval by constructing semantic code words for efficient large scale face retrieval. Mainly we propose two methods named Attribute- Enhanced Sparse Coding and Attribute Embedded Inverted Indexing. These two methods will improve the face retrieval in the online and offline stages.

References
[1] Bor-Chun Chen, Yan-Ying Chen, Yin-Hsi Kuo, Winston H. Hsu, “Scalable Face Image Retrieval using Attribute-Enhanced Sparse Codewords”, IEEE TRANSACTIONS ON MULTIMEDIA, 2013.
[2] M.Balaganesh, N.Arthi, “Image Retrieval Using Attribute Enhanced Sparse Code Words.”, International Journal of Innovative Research in Science, Engineering and Technology, 2014
[3] Manisha Bhisekar, Prakash Patil, Prajakta Deshmane, “Enhanced Sparse Codeword Based Efficient Method For Large Scale Face Image Retrieval”, Proceedings of National Conf. on Recent Innovations in Science Engineering & Technology, 2014
[4] U. Park and A. K. Jain, “Face matching and retrieval using soft biometrics,” IEEE Transactions on Information Forensics and Security, 2010.
[5] Z. Wu, Q. Ke, J. Sun, and H.-Y. Shum, “Scalable face image retrieval with identity-based quantization and multi-reference re-ranking,” IEEE Conference on Computer Vision and Pattern Recognition, 2010.
[6] B.-C. Chen, Y.-H. Kuo, Y.-Y. Chen, K.-Y. Chu, and W. Hsu, “Semisupervised face image retrieval using sparse coding with identity constraint,” ACM Multimedia, 2011.
[7] M. Douze and A. Ramisa and C. Schmid, “Combining Attributes and Fisher Vectors for Efficient Image Retrieval,”IEEE Conference on Computer Vision and Pattern Recognition, 2011.

Keywords
Face image, human attributes, content-based image retrieval, Attribute enhanced sparse codeword’s, attribute embedded inverted indexing.