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A real 3d scene rendering optimization method based on region of interest and viewing frustum prediction in virtual reality

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International Journal of digital Earth 2022年第1期15卷 1081-1100页

作者： Pei dang Jun Zhu Jianlin Wu Weilian Li Jigang You Lin Fu Yiqun Shi Yuhang Gong Faculty of Geosciences and Environmental Engineering Southwest Jiaotong UniversityChengduPeople’s Republic of China Institute of Geodesy and Geoinformation University of BonnBonnGermany Faculty of Civil Engineering Southwest Jiaotong UniversityChengduPeople’s Republic of China department of Natural Resources of Sichuan Province Sichuan Institute of Land Science and TechnologyChengduPeople’s Republic of China

As an important technology of digital construction,real 3d models can improve the immersion and realism of virtual reality(VR)*** large amount of data for real 3d scenes requires more effective rendering methods,but the current rendering optimization methods have some defects and cannot render real 3d scenes in virtual *** this study,the location of the viewing frustum is predicted by a Kalman filter,and eye-tracking equipment is used to recognize the region of interest(ROI)in the ***,the real 3d model of interest in the predicted frustum is rendered *** experimental results show that the method of this study can predict the frustrum location approximately 200 ms in advance,the prediction accuracy is approximately 87%,the scene rendering efficiency is improved by 8.3%,and the motion sickness is reduced by approximately 54.5%.These studies help promote the use of real 3d models in virtual reality and ROI recognition *** future work,we will further improve the prediction accuracy of viewing frustums in virtual reality and the application of eye tracking in virtual geographic scenes.

关键词： real 3d scene virtual reality Kalman filter region of interest viewing frustum

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