A Kalman-filtering method for 3D camera motion estimation from image sequences

Eung-Tae Kim, Jong-Ki Han, Hyung-Myung Kim
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引用次数: 14

Abstract

In this paper, we describe a method for estimating and compensating 3D camera motion in image sequences for applications to the video coding system. To effectively estimate camera motion parameters (zoom, pan, tilt, swing, and focal length) from image sequences, we propose a new linear motion parameter equation and use the Kalman filtering method to solve it. Unlike the existing linear techniques, the proposed linear method accurately estimates the large rotation angles and the focal length. Experimental results show that the proposed method outperforms the conventional linear methods, especially for a large rotation angle.
基于图像序列的三维摄像机运动估计的卡尔曼滤波方法
本文描述了一种用于视频编码系统的图像序列中三维摄像机运动的估计和补偿方法。为了从图像序列中有效地估计摄像机的运动参数(变焦、平移、倾斜、摆动和焦距),我们提出了一个新的线性运动参数方程,并使用卡尔曼滤波方法对其进行求解。与现有的线性方法不同,本文提出的线性方法能够准确地估计出大旋转角度和焦距。实验结果表明,该方法优于传统的线性方法,特别是在大旋转角度下。
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