计算机视觉
人工智能
稳健性(进化)
计算机科学
视野
迭代重建
图像分辨率
虚拟映像
摄像机自动校准
三维重建
摄像机切除
计算机图形学(图像)
生物化学
化学
基因
作者
Yuxuan Chen,Ben Wang,Qiongwei Li,Zhong Yu-jun,Yi Jin,Ce Zhu
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:71: 1-12
被引量:4
标识
DOI:10.1109/tim.2022.3165271
摘要
The 3-D shape reconstruction is a hot topic in computational imaging and many related techniques have been developed. However, most of these techniques have a limited field-of-view (FOV), which results in difficulties on general application. In this article, an FOV-enlarged single-camera 3-D shape reconstruction system is proposed. By placing a saccade mirror in the light path, the proposed system generates a series of virtual cameras and reconstructs the object with multiview images. As the virtual cameras have the same resolution with the real camera, the system gets a larger FOV for reconstruction without sacrificing image resolution. Besides, compared with conventional stereovision systems, the proposed system gives a prior of postures of virtual cameras and simplifies the calibration procedure of extrinsic parameters, which makes it a compact and economical system for application. Reconstruction experiments demonstrate that the proposed system provides an FOV-enlarged and accurate 3-D shape reconstruction. Furthermore, the robustness of the system to environmental conditions is also verified by real-life experiments.
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