基于视角优化的便携像机视频去抖算法
Orientation Optimization Based 3D Video Stabilization for Portable Cameras

作者: 杨诚笃 , 许宏丽 :北京交通大学计算机学院,北京; 尹辉 , 黄华 :北京交通大学计算机学院,北京;北京交通大学交通数据分析与挖掘北京市重点实验室,北京;

关键词: 视频去抖视角优化多项式拟合Video Stabilization Rotation Optimization Polynomial Curve-Fitting

摘要: 针对便携式摄像机的视频去抖问题,本文提出一种基于摄像机视角优化的视频去抖算法。首先,通过struc- ture-from-motion算法估计摄像机连续运动位姿。其次,基于摄像机的空间位置进行多项式曲线拟合,得到摄像机运动的虚拟路径。然后,通过向量插值平滑视角朝向。最后,基于相机运动平滑曲线与平滑视角对视频帧进行筛选和修正实现视频去抖。实验证明,该算法很好地解决了2D去抖算法对摄像机运动参数估计不足的问题。在真实数据集上的实验结果验证了本文算法在针对便携式摄像机视频数据的去抖有效性。

Abstract: We present a novel view optimization algorithm in the paper for video stabilization. Most existing 2D video stabilization methods may fail to estimate the motion parameters of cameras. In order to solve above problems, we propose a video stabilization method based on 3D technology. Firstly, recovers the original 3D camera motion using the structure-from-motion system. Then, a virtual camera path is computed by polynomial curve fitting. And then, smoothes the view orientation by vectorial interpolation. Finally, corrects the frames which selected in conformity with the smooth- ing location and orientation of cameras. Our experiments on stabilizing challenging videos of real scenes demonstrate the effectiveness of our technique.

文章引用: 杨诚笃 , 许宏丽 , 尹辉 , 黄华 (2015) 基于视角优化的便携像机视频去抖算法。 计算机科学与应用, 5, 436-444. doi: 10.12677/CSA.2015.512055

参考文献

[1] [1] Hartley, R. and Zisserman, A. (2003) Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge.

[2] 宋利, 周源华, 周军. 基于运动矢量的视频去抖动算法[J]. 上海交通大学学报, 2004(z1): 63-66.

[3] Song, L., Zhou, Y.H. and Zhou, J. (2005) Robust Video Stabilization Based on Motion Vectors. Journal of Shanghai University (English Edition), 9, 46-51.
http://dx.doi.org/10.1007/s11741-005-0103-1

[4] 徐理东, 林行刚. 视频抖动矫正中全局运动参数的估计[J]. 清华大学学报: 自然科学版, 2007, 47(1): 92-95.

[5] 赵文华, 姚天翔, 叶秀清, 等. RANSAC算法在视频去抖动中的应用[J]. 电路与系统学报, 2005, 10(4): 91-94.

[6] 於俊, 汪增福. 基于SIFT特征匹配的实时鲁棒视频去抖系统[J]. 系统工程与电子技术, 2014, 36(2).

[7] Liu, S., Yuan, L., Tan, P. and Sun, J. (2013) Bundled Camera Paths for Video Stabilization. ACM Transactions on Graphics (TOG), 32, 78.
http://dx.doi.org/10.1145/2461912.2461995

[8] Liu, F., Gleicher, M., Jin, H. and Agarwala, A. (2009) Content-Preserving Warps for 3D Video Stabilization. ACM Transactions on Graphics (TOG), 28, 44.

[9] Kopf, J., Cohen, M.F. and Szeliski, R. (2014) First-Person Hyper-Lapse Videos. ACM Transactions on Graphics (TOG), 33, 78.
http://dx.doi.org/10.1145/2601097.2601195

[10] Ryu, Y.G., Roh, H.C. and Chung, M.J. (2010) 3D Video Stabi-lization for Humanoid Eyes Using Vision and Inertial Sensors Inspired by Human VOR. IEEE International Conference on Robotics and Biomimetics (ROBIO), 1780-1785.

[11] Buehler, C., Bosse, M. and McMillan, L. (2001) Non-Metric Image-Based Rendering for Video Stabilization. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, II-609.
http://dx.doi.org/10.1109/cvpr.2001.991019

[12] Snavely, N., Seitz, S.M. and Szeliski, R. (2006) Photo Tourism: Exploring Photo Collections in 3D. ACM Transactions on Graphics (TOG), 25, 835-846.

[13] Shoemake, K. (1985) Animating Rotation with Quaternion Curves. ACM SIGGRAPH Computer Graphics, 19, 245-254.
http://dx.doi.org/10.1145/325165.325242

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