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首页> 外文会议>Conference on Machine Vision Applications in Industrial Inspection Ⅹ Jan 21-22, 2002, San Jose, USA >The computation of the real-time camera motion through a correlation and a dynamic model of system
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The computation of the real-time camera motion through a correlation and a dynamic model of system

机译：通过相关性和系统动态模型计算实时摄像机运动

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摘要

Camera ego-motion is computed utilizing optical flows which are obtained from sparsely located feature points, where the corresponding points are determined through the information fusion of the correlation and the system model-based prediction. Since the ego-motion of the camera is obtained utilizing optical flows, the accuracy of recognized motion depends highly on the correctness of optical flows. Therefore, the ego-motion utilizing feature-based optical flows are more reliable than those of other points due to the distinctive characteristic of feature points. The technical bottleneck of this category of solution is the matching of corresponding points. In this paper, the correlation and prediction is fused to determine trustable matching pairs. For better prediction, system dynamic model is employed. The effect of the proposed algorithm has been shown through the motion estimation of the camera installed on a dynamic system.
机译：利用从稀疏定位的特征点获得的光流来计算相机的自我运动，其中通过相关性的信息融合和基于系统模型的预测来确定相应的点。由于照相机的自我运动是利用光流获得的，因此识别运动的准确性在很大程度上取决于光流的正确性。因此，由于特征点的独特特性，利用基于特征的自我运动比其他点更可靠。此类解决方案的技术瓶颈是对应点的匹配。在本文中，将相关性和预测融合在一起以确定可信赖的匹配对。为了更好的预测，采用系统动态模型。通过对动态系统上安装的摄像头的运动估计，已显示了所提出算法的效果。

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