Real-time correction method of image distortion in virtual reality scene

Dan Zhao; JinDe Huang

doi:10.1117/12.2631417

18 March 2022 Real-time correction method of image distortion in virtual reality scene

Dan Zhao, JinDe Huang

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121680N (2022) https://doi.org/10.1117/12.2631417
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

In order to improve the visual effect of the image and solve the problems of long image correction time and low accuracy of image correction in traditional methods, a real-time correction method for image distortion in virtual reality scenes is proposed. The deep learning method is used to classify the virtual scene. After determining the type of virtual scene, the Hough transform method is used to extract the image distortion target contour, and the edge detection algorithm is used to make the position of the target edge reach the sub-pixel level. Based on the edge distortion detection, a distortion model that can describe the image distortion is constructed, and the image distortion is corrected. The experimental results show that the correction time of this method is short, the correction accuracy is high, and the visual effect of the corrected image is good, which fully verifies the effectiveness of this method.

Citation Download Citation

Dan Zhao and JinDe Huang "Real-time correction method of image distortion in virtual reality scene", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121680N (18 March 2022); https://doi.org/10.1117/12.2631417

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