【摘要】 针对传统视频稳像算法无法兼顾高质量稳像和低延时的问题,提出李群流形上卡尔曼滤波的实时视频稳像算法.将视频帧间运动分解为旋转分量和平移分量.旋转分量由陀螺仪数据计算的旋转矩阵表示,平移分量由视频帧间匹配得到的平移矩阵表示,旋转矩阵的序列和平移矩阵的序列分别对应于李群流形上的运动路径.利用李群流形上的卡尔曼滤波分别对旋转分量和平移分量进行平滑.最终通过运动补偿获得稳定的视频帧序列.实验表明,文中算法能够兼顾延时和稳像效果,可以在移动端实现高质量的在线视频稳像.更多还原

【Abstract】 The traditional video stabilization algorithms cannot achieve good performance with a low latency. Aiming at this problem, an algorithm is proposed using the Lie group manifold based Kalman filter to stabilize videos in real time. The video frame motion is separated into rotation component and translation component. The rotation component can be represented by the rotation matrix obtained via the gyroscope data, while the translation component is provided by the translation matrix computed by the matching between video frames. Both the sequence of the rotation matrices and the translation matrices can form the motion paths on the Lie group manifold. Therefore, the Lie group manifold based Kalman filter is used to smooth the rotation and translation component, respectively. Finally, the video frame sequence can be stabilized by the motion compensation. The experimental results show that the proposed algorithm achieves high online real-time video stabilization performance on the mobile device.更多还原