用于运动估计的视觉船体露头点提取

M. Toyoura, M. Iiyama, K. Kakusho, M. Minoh
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引用次数: 1

摘要

本文讨论了用体交法重建刚体运动物体的三维形状。当物体作刚性运动时,摄像机会随时改变与物体的相对位置。为了正确估计运动,我们在重建的三维形状上提出了新的特征点,称为露头点。这些点保证位于物体的真实表面上。如果能正确估计物体的刚体运动,则不同时刻的摄像机实际上充当了不同位置的摄像机。在不增加相机数量的情况下,利用这些时间序列相机可以提高重建三维形状的精度。基于这一思想,我们从有限数量的相机获得的图像中重建运动物体的精确形状。因此,我们可以从时间序列的图像中获得精确的形状
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extraction of Outcrop Points from Visual Hulls for Motion Estimation
In this article, we discuss 3D shape reconstruction of an object in a rigid motion with the volume intersection method. When the object moves rigidly, the cameras change their relative positions to the object at every moment. To estimate the motion correctly, we propose new feature points called outcrop points on the reconstructed 3D shape. These points are guaranteed to be located on the real surface of the object. If the rigid motion of the object can be correctly estimated, cameras at different moments serve as the cameras in different positions virtually. With these cameras in time sequences, we can increase accuracy of the reconstructed 3D shape without increasing the number of cameras. Based on this idea, we reconstruct an accurate shape of the object in motion from images obtained by limited number of cameras. As the result, we can acquire an accurate shape from images in time sequences
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