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Tagging and Clustering of Objects in Videos

Published on May 2012 by Vikrant Gangan, C. N. S. Sisma, Monisha Menon, Aditya Gupta
journal_cover_thumbnail

National Conference on Recent Trends in Computing
Foundation of Computer Science USA
NCRTC - Number 3
May 2012
Authors: Vikrant Gangan, C. N. S. Sisma, Monisha Menon, Aditya Gupta
0011ed51-9841-4093-a253-c66dbc41995c

Vikrant Gangan, C. N. S. Sisma, Monisha Menon, Aditya Gupta . Tagging and Clustering of Objects in Videos. National Conference on Recent Trends in Computing. NCRTC, 3 (May 2012), 23-25.

@article{
author = { Vikrant Gangan, C. N. S. Sisma, Monisha Menon, Aditya Gupta },
title = { Tagging and Clustering of Objects in Videos },
journal = { National Conference on Recent Trends in Computing },
issue_date = { May 2012 },
volume = { NCRTC },
number = { 3 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 23-25 },
numpages = 3,
url = { /proceedings/ncrtc/number3/6533-1023/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Recent Trends in Computing
%A Vikrant Gangan
%A C. N. S. Sisma
%A Monisha Menon
%A Aditya Gupta
%T Tagging and Clustering of Objects in Videos
%J National Conference on Recent Trends in Computing
%@ 0975-8887
%V NCRTC
%N 3
%P 23-25
%D 2012
%I International Journal of Computer Applications
Abstract

"Tagging" in videos is an extension of the image tagging application. Just as people can be tagged in images, a system can be developed to carry out tagging in video clips. Using this, people can automatically be identified ("tagged") wherever they are present in a video clip. The paper discusses the design of the system which identifies the real world objects in a video clip. The object to be searched can be provided by the user in the form of an image. The object is specified by a user outlining it in an image, and the object is then delineated in the retrieved shots. The aim is to detect and track presence of required objects in a video and for thesearching to be view-point invariant. Finally, the searched object can be tracked throughout the video by clustering all of its occurrences into a single video. This can be used for analyzing any possible changes the object might have undergone during the length of the video.

References
  1. Jia Wang and Wei Tsang Ooi, "Detecting Static Objects in a Busy Scene," Department of Computer Science, Cornell University, Ithaca, Technical Report TR99-1730, Feb. 8, 1999.
  2. "Automatic image annotation," http://en. wikipedia. org/wiki/Automatic_image_annotation, June 20, 2011.
  3. "Content-based image retrieval," http://en. wikipedia. org/wiki/Content-based_image_retrieval. html, September 16, 2011.
  4. "Facebook Wins Patents For Tagging in Photos, Other Digital Media," http://www. insidefacebook. com/2011/05/17/facebook-patent-photo-tagging. html, May 17, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Tagging Clustering Searching Object Video Frames