Location of feature points in 3D reconstruction of multi vision color image based on principal component analysis

FENG, Huan-ping and ZHANG, Li-wei (2020) Location of feature points in 3D reconstruction of multi vision color image based on principal component analysis. In: Mobimedia 2020, 27-28 August 2020, Cyberspace.

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Abstract

Traditional image feature point location methods, due to the existence of calculation errors, lead to the accuracy of the location of feature points decreased, so based on principal component analysis, a new multi vision color image 3D reconstruction feature point location method is proposed.In this method, the gray level of color image is transformed by principal component analysis, and the color features of the image are obtained according to the gray level difference of local color areas;According to the changing characteristics of environment light coefficient and diffuse reflection light coefficient, the control parameters affecting the three-dimensional light shadow effect of multi vision color image are set;The least square method is used to eliminate the position error of feature points, and according to the confidence degree of association rules between nodes, more accurate feature point positioning results are obtained.Experimental results show that the accuracy of the proposed method is 11.27% higher than that of the traditional method. Therefore, the proposed method is more suitable for feature point location.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: keywords principal component analysis; multi vision color image 3d reconstruction; feature point location
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor I.
Date Deposited: 04 Feb 2021 14:22
Last Modified: 04 Feb 2021 14:22
URI: https://eprints.eudl.eu/id/eprint/877

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