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Performance of SIFT based Video Retrieval

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CONTRIBUTORS:
  Author Shradha Gupta
  Author Prof. Neetesh Gupta
  Author Dr. Bhupendra Verma
JOURNAL:
  International Journal on Computer Science and Engineering (IJCSE), 3(6), 2565 - 2571.
YEAR: 2011
PUB TYPE: Journal Article
SUBJECT(S): Video retrieval; segmentation; SIFT; Mahalanobis Distance.
DISCIPLINE: Computer Science
HTTP: http://www.enggjournals.com/ijcse/doc/IJCSE11-03-06-046.pdf
LANGUAGE: English
PUB ID: 103-489-264 (Last edited on 2011/06/19 22:27:10 GMT-6)
SPONSOR(S):
 
ABSTRACT:
Video has become an important element of multimedia computing and communication environments, with applications as varied as broadcasting, education, publishing and military intelligence. In Video Retrieval system, each video that is stored in the database has its features extracted and compared to the features of the query image. Proposed work is to retrieve video from the database by giving query as an object. Video is firstly converted into frames, these frames are then segmented and an object is separated from the image. Then features are extracted from object image by using SIFT features. Features of the video database obtained by the segmentation and feature extraction using SIFT feature are matched by Mahalanobis Distance. In this paper experiments are done on different samples of images. Result is also calculated after illumination changes in object.
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