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Automatic feature point extraction and tracking in image sequences for unknown camera motion

机译:图像序列中的自动特征点提取和跟踪,用于未知摄像机的运动

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An automatic ego motion compensation based feature detection and correspondence algorithm is presented. For image sequences taken from a moving camera, feature displacement over consecutive frames can be approximately decomposed into two components: the displacement due to camera motion, which can be compensated for by image rotation, scaling, and translation; and the displacement due to object motion and/or perspective projection. The authors introduce a two-step approach. First, the motion of the camera is compensated for by 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 for a stationary camera. Feature points are detected using a Gabor wavelet decomposition and a local interaction based algorithm. Methods for subpixel accuracy feature matching and tracking are introduced. Experimental results on a real image sequence are presented.
机译:提出了一种基于自我运动补偿的自动特征检测与对应算法。对于从移动相机拍摄的图像序列,连续帧上的特征位移可以大致分解为两个分量:相机运动引起的位移,可以通过图像旋转,缩放和平移来补偿;以及由于物体运动和/或透视投影而产生的位移。作者介绍了一种两步法。首先,通过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,并且就好像固定相机一样解决了特征对应问题。使用Gabor小波分解和基于局部交互的算法检测特征点。介绍了亚像素精度特征匹配与跟踪的方法。提出了在真实图像序列上的实验结果。

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