首页> 外文期刊>International Journal of Computer Vision >AUTOMATIC FEATURE POINT EXTRACTION AND TRACKING IN IMAGE SEQUENCES FOR ARBITRARY CAMERA MOTION
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AUTOMATIC FEATURE POINT EXTRACTION AND TRACKING IN IMAGE SEQUENCES FOR ARBITRARY CAMERA MOTION

机译:任意相机运动的图像序列中特征点的自动提取和跟踪

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摘要

An automatic egomotion compensation based point correspondence algorithm is presented. A basic problem in autonomous navigation and motion estimation is automatically detecting and tracking features in consecutive frames, a challenging problem when camera motion is significant. In general, feature displacements between consecutive frames can be approximately decomposed into two components: (i) displacements due to camera motion which can be approximately compensated by image rotation, scaling, and translation; (ii) displacements due to object motion and/or perspective projection. In this paper, we introduce a two-step approach: First, the motion of the camera is compensated using a computational vision based image registration algorithm. Then consecutive frames are transformed to the same coordinate system and the feature correspondence problem is solved as though tracking moving objects for a stationary camera. Methods of subpixel accuracy feature matching, tracking and error analysis are introduced. The approach results in a robust and efficient algorithm. Results on several real image sequences are presented. [References: 21]
机译:提出了一种基于自我补偿的自动点对应算法。自主导航和运动估计中的一个基本问题是自动检测和跟踪连续帧中的特征,这在相机运动很重要时是一个具有挑战性的问题。通常,连续帧之间的特征位移可以大致分解为两个分量:(i)摄像机运动引起的位移,可以通过图像旋转,缩放和平移近似补偿; (ii)由于物体运动和/或透视投影而产生的位移。在本文中,我们介绍了一种两步方法:首先,使用基于计算视觉的图像配准算法来补偿摄像机的运动。然后将连续的帧转换为相同的坐标系,并解决了特征对应问题,就好像为固定摄像机跟踪运动对象一样。介绍了亚像素精度特征匹配,跟踪和误差分析的方法。该方法产生了鲁棒且有效的算法。呈现了几个真实图像序列的结果。 [参考:21]

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