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Panoramic Stereo Imaging of a Bionic Compound-Eye Based on Binocular Vision

机译:基于双目视觉的仿生复合眼的全景立体成像

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摘要

With the rapid development of the virtual reality industry, one of the bottlenecks is the scarcity of video resources. How to capture high-definition panoramic video with depth information and real-time stereo display has become a key technical problem to be solved. In this paper, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed. Combined with the real-time processing algorithm of multi detector mosaic panoramic stereo imaging image, a panoramic stereo real-time imaging system is developed. Firstly, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed, and the space coordinate calibration platform of ultra-high precision panoramic camera based on theodolite angle compensation function is constructed. The projection matrix of adjacent cameras is obtained by solving the imaging principle of binocular stereo vision. Then, a real-time registration algorithm of multi-detector mosaic image and Lucas-Kanade optical flow method based on image segmentation are proposed to realize stereo matching and depth information estimation of panoramic imaging, and the estimation results are analyzed effectively. Experimental results show that the stereo matching time of panoramic imaging is 30 ms, the registration accuracy is 0.1 pixel, the edge information of depth map is clearer, and it can meet the imaging requirements of different lighting conditions.
机译:随着虚拟现实行业的快速发展,其中一个瓶颈是视频资源的稀缺。如何使用深度信息和实时立体声显示器捕获高清全景视频已成为要解决的关键技术问题。本文提出了基于双目立体视觉的全景成像光学优化设计方案。结合多检测器镶嵌全景立体声成像图像的实时处理算法,开发了全景立体声实时成像系统。首先,提出了基于双目立体视觉视觉的全景成像的光学优化设计方案,构建了基于经纬仪角度补偿功能的超高精度全景摄像机的空间坐标校准平台。通过求解双目立体声视觉的成像原理来获得相邻摄像机的投影矩阵。然后,提出了一种基于图像分割的多检测器马赛克图像的实时登记算法和基于图像分割的Lucas-Kanade光学流量方法来实现全景成像的立体声匹配和深度信息估计,有效地分析估计结果。实验结果表明,全景成像的立体声匹配时间为30毫秒,登记精度为0.1像素,深度图的边缘信息更清晰,可以满足不同照明条件的成像要求。

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