用计算机视觉同时估计物体的三维形状和运动

J. Schick, E. Dickmanns
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引用次数: 34

摘要

讨论了一种基于4d方法的实时计算机视觉递归估计方法,用于同时确定物体的三维形状参数和运动状态。识别过程利用结构给定的形状模型和由差分方程给出的运动模型。这允许将图像分析限制为仅对序列的最后一帧进行特征评估;图像之间没有差异,但空间运动分量(满足平面运动约束)可以直接恢复,而无需显式反转成像过程的透视投影方程。物体识别已经被限制在一个结构良好,但一般动态场景开始:道路交通与有限类别的车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simultaneous estimation of 3D shape and motion of objects by computer vision
A recursive estimation method based on the 4D-approach to real-time computer vision for simultaneously determining both 3D shape parameters and motion state of objects is discussed. The recognition processes exploit structurally given shape models and motion models given by difference-equations. This allows to confine the image analysis to feature evaluation of the last frame of the sequence only; no differencing between images has to be done, yet the spatial motion components (satisfying planar motion constraints) are recovered directly without inverting the perspective projection equations of the imaging process explicitly. Object recognition has been confined to a well structured, but otherwise general dynamic scene for the beginning: road traffic with a limited class of vehicles.<>
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