Color-SIFT model: a robust and an accurate shot boundary detection algorithm

M. Sharmila Kumari; B. H. Shekar

doi:10.1117/12.856328

26 February 2010 Color-SIFT model: a robust and an accurate shot boundary detection algorithm

M. Sharmila Kumari, B. H. Shekar

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75463S (2010) https://doi.org/10.1117/12.856328
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

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.

Citation Download Citation

M. Sharmila Kumari and B. H. Shekar "Color-SIFT model: a robust and an accurate shot boundary detection algorithm", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75463S (26 February 2010); https://doi.org/10.1117/12.856328

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