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Proceedings Paper

Color-SIFT model: a robust and an accurate shot boundary detection algorithm
Author(s): M. Sharmila Kumari; B. H. Shekar
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Paper Abstract

In this paper, a new technique called color-SIFT model is devised for shot boundary detection. Unlike scale invariant feature transform model that uses only grayscale information and misses important visual information regarding color, here we have adopted different color planes to extract keypoints which are subsequently used to detect shot boundaries. The basic SIFT model has four stages namely scale-space peak selection, keypoint localization, orientation assignment and keypoint descriptor and all these four stages were employed to extract key descriptors in each color plane. The proposed model works on three different color planes and a fusion has been made to take a decision on number of keypoint matches for shot boundary identification and hence is different from the color global scale invariant feature transform that works on quantized images. In addition, the proposed algorithm possess invariance to linear transformation and robust to occlusion and noisy environment. Experiments have been conducted on the standard TRECVID video database to reveal the performance of the proposed model.

Paper Details

Date Published: 26 February 2010
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75463S (26 February 2010); doi: 10.1117/12.856328
Show Author Affiliations
M. Sharmila Kumari, P. A. College of Engineering (India)
B. H. Shekar, Mangalore Univ. (India)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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