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3D Object Localization Using 2D Estimates for Computer Vision Applications

机译:计算机视觉应用中基于二维估计的三维物体定位

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Computer vision based applications have received notable attention globally due to the interaction with the physical world. In this paper, a novel method for object localization based on camera calibration and pose estimation is discussed. The 3-dimensional (3D) coordinates are computed by taking multiple 2-dimensional (2D) images from different view that meets the requirement in camera calibration process. Several number of steps are involved in camera calibration including estimation of intrinsic and extrinsic parameters for the removal of lens distortion, estimation of object’s size and camera location. Besides, a technique to estimate the 3D pose using 2D images is proposed and the results of camera parameters and localization are applied for the 3D reconstruction. The hardware implementation of the proposed approach is implemented on HP core i5 with the MATLAB support packages and experimental results are validated for both camera calibration and pose estimation.
机译:由于与物理世界的交互作用,基于计算机视觉的应用受到了全球的关注。本文讨论了一种基于摄像机标定和姿态估计的目标定位新方法。三维(3D)坐标是通过从不同视图获取多个二维(2D)图像来计算的,这些图像满足摄像机标定过程中的要求。摄像机标定涉及多个步骤,包括估计去除镜头畸变的内在和外在参数、估计物体大小和摄像机位置。此外,提出了一种利用二维图像估计三维姿态的方法,并将摄像机参数和定位结果应用于三维重建。该方法的硬件实现在HP core i5上通过MATLAB支持包实现,并对摄像机标定和姿态估计的实验结果进行了验证。

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