Research Article
Study and Analysis of Search based Face Annotation using Vision Cascade Object Detector
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 148 - Issue 8 |
| Published: Aug 2016 |
| Authors: Pankaj J. Kokane, B. M. Patil |
10.5120/ijca2016911236
|
Pankaj J. Kokane, B. M. Patil . Study and Analysis of Search based Face Annotation using Vision Cascade Object Detector. International Journal of Computer Applications. 148, 8 (Aug 2016), 9-11. DOI=10.5120/ijca2016911236
@article{ 10.5120/ijca2016911236,
author = { Pankaj J. Kokane,B. M. Patil },
title = { Study and Analysis of Search based Face Annotation using Vision Cascade Object Detector },
journal = { International Journal of Computer Applications },
year = { 2016 },
volume = { 148 },
number = { 8 },
pages = { 9-11 },
doi = { 10.5120/ijca2016911236 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2016
%A Pankaj J. Kokane
%A B. M. Patil
%T Study and Analysis of Search based Face Annotation using Vision Cascade Object Detector%T
%J International Journal of Computer Applications
%V 148
%N 8
%P 9-11
%R 10.5120/ijca2016911236
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Face recognition presents a various challenges in the field of image analysis and computer vision, and large amount of work has been done over the last few years because of its applications in various domains. Mining web facial images on the internet has evolved as a promising model towards auto face annotation. Content-based image retrieval (CBIR) systems needs users to give low-level visual content images as query and then retrieve similar top matching images from database. The technique also aims to investigates framework of search-based face annotation (SBFA) by mining weakly labeled facial images that are freely available on the World Wide Web (WWW). This work presents automated face annotation that aims to automatically detect human faces from a photo and further annotate the faces with the corresponding human names.
References
- IEEE Transactions On Knowledge And Data Engineering, VOL. 26, NO.1, JANUARY 2014 on Mining Weakly Labeled Web Facial Images for Search-Based Face Annotation.
- International Journal of Computer Science Engineering and Technology( IJCSET) | October 2014 | VOL.4, Issue 10,253-255 Survey on Unsupervised Mining Weakly Labeled Web Facial Images for Search-Based Face Annotation.
- G. B. Huang M, Ramesh, T. Berge abd E. Lerned-Miller. "Labeled Faces in the wild: A Database for studying Face Recognisation in Untrested Environment. 2007
- Margarita Osadchy, Benny Pinkas University of Haifa “SCiFI – A System for Secure Face Identification”
- International Journal of Advanced Science and Technology Vol. 50, January, 2013 Raikoti Sharanabasappa1 and Sanjaypande M. B. “ A Unique Document Security Technique using Face Biometric Template”
- IEEE Transactions On Knowledge And Data Engineering, VOL. 25, NO. 3, MARCH 2013 Annotating Search Results from Web Databases.
- M. Zhao, J. Yagnik, H. Adam, and D. Bau, “Large Scale Learning and Recognition of Faces in Web Videos," Proc. IEEE Eighth Intl Conf. Automatic Face and Gesture Recognition (FG), pp. 1-7, 2008.
- International ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp. 111-118, 2007 J. Fan, Y. Gao, and H. Luo, “Hierarchical Classification for Automatic Image Annotation,” Proc. 30th Ann.
- International ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp. 1097-1098,2011Z.Lin,G.Ding,andJ.Wang,“Image Annotation Based on Recommendation Model,” Proc. 34th.
- IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 3, pp. 394-410, Mar. 2007 Carneiro, A.B. Chan, P. Moreno, and N. Vasconcelos, “Supervised Learning of Semantic Classes for Image Annotation and Retrieval".
Index Terms
Keywords