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JBE, vol. 23, no. 4, pp.559-573, July, 2018
Parameter Analysis for Time Reduction in Extracting SIFT Keypoints in the Aspect of Image Stitching
Won-Jun Moon, Young-Ho Seo, and Dong-Wook Kim
C.A E-mail: email@example.com
Recently, one of the most actively applied image media in the most fields such as virtual reality (VR) is omni-directional or panorama image. This image is generated by stitching images obtained by various methods. In this process, it takes the most time to extract keypoints necessary for stitching. In this paper, we analyze the parameters involved in the extraction of SIFT keypoints with the aim of reducing the computation time for extracting the most widely used SIFT keypoints. The parameters considered in this paper are the initial standard deviation of the Gaussian kernel used for Gaussian filtering, the number of gaussian difference image sets for extracting local extrema, and the number of octaves. As the SIFT algorithm, the Lowe scheme, the originally proposed one, and the Hess scheme which is a convolution cascade scheme, are considered. First, the effect of each parameter value on the computation time is analyzed, and the effect of each parameter on the stitching performance is analyzed by performing actual stitching experiments. Finally, based on the results of the two analyses, we extract parameter value set that minimize computation time without degrading.
Keyword: omni-directional image, image stitching, SIFT keypoints, SIFT parameters, Gaussian pyramid
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