Fast Global Motion Estimation Algorithm Based on Affine Transformation

WANG Si-jun; ZHAO Jian; HAN Xi-zhen

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Fast Global Motion Estimation Algorithm Based on Affine Transformation

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- Fast Global Motion Estimation Algorithm Based on Affine Transformation
- Chinese Journal of Liquid Crystals and Displays Vol. 27, Issue 2, Pages: 263-266(2012)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院研究生院北京,100049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Received：20 May 2011，
  
  Revised：15 June 2011，
  
  Published Online：15 April 2012，
  
  Published：15 April 2012
- 稿件说明：
移动端阅览
王思珺, 赵建, 韩希珍. 基于仿射变换的快速全局运动估计算法[J]. 液晶与显示, 2012,(2): 263-266

WANG Si-jun, ZHAO Jian, HAN Xi-zhen. Fast Global Motion Estimation Algorithm Based on Affine Transformation[J]. , 2012,(2): 263-266
王思珺, 赵建, 韩希珍. 基于仿射变换的快速全局运动估计算法[J]. 液晶与显示, 2012,(2): 263-266 DOI：

WANG Si-jun, ZHAO Jian, HAN Xi-zhen. Fast Global Motion Estimation Algorithm Based on Affine Transformation[J]. , 2012,(2): 263-266 DOI：

摘要

全局运动估计是计算机视觉、视频处理等领域广泛采用的手段之一。为了降低全局运动估计计算复杂度

提出一种基于像素梯度的全局运动估计方法。就运动模型而言

采用了复杂性与准确性较好均衡的六参数仿射模型。为了提高计算速度

采用了两层金字塔进行多分辨率计算

而且在每层迭代计算中都抽取梯度较大的特征点进行计算

同时结合了高斯-牛顿优化计算方法。实验验证了提出的全局运动估计算法的计算效率和精度。

Abstract

Global Motion Estimation is an important tool widely used in computer vision

video processing

and other fields. To reduce the computational complexity of global motion estimation

a global motion estimation method based on the pixel gradient strategy was proposed. With regard to global motion models

six-parameter affine model is adopted because of its reasonable tradeoff between complexity and accuracy. In order to accelerate the algorithm

two-level pyramid is utilized in the calculation. It uses those gradient bigger pixels in the calculation of every pyramid level

and combines Gauss-Newton algorithm. The extensive experiments show that the proposed method is efficient and robust in terms of both computational complexity and accuracy.

关键词

Keywords

references

Mahmoud H, Bayoumi M. An efficient low-bit rate adaptive mesh-based motion compensation technique // Proc. 2nd Int. Workshop on Digital and Computational Video. Tampa, Florida, USA:IEEE Computer Society, 2001:164-172.[2] Yosi K, Amir A. Fast gradient methods based on global motion estimation for video compression [J]. IEEE Trans. Circuit Syst. Video Technol., 2003, 13(4):300-309.[3] Dufaux F, Konrad J. Efficient, robust, and fast global motion estimation for video coding [J]. IEEE Transactions on Image Processing, 2000, 9(3):497-501.[4] 俞天力,章毓晋.基于全局运动信息的视频检索技术 [J]. 电子学报, 2001,29(12A):1794-1798.[5] Rath G B, Makur A. Iterative least squares and compression based estimations for a four-parameter linear global motion model and global motion compensation [J]. IEEE Transactions on Circuits and Systems for Video Techno-logy, 1999, 9(7):1075-1099.[6] Bin Qi, Ghazal M, Amer A. Robust global motion estimation oriented to video object segmentation [J]. IEEE Transactions on Image Processing, 2008,17(6):958-967.[7] Keller Y, Averbuch A. Fast gradient methods based on global motion estimation for video compression [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2003, 13(4):300-309.[8] Wang D, Wang L. Fast and robust algorithm for global motion estimation // Proc SPIE Conf on Visual Communications and Image Processing(VCIP), San Jose, CA, USA:SPIE 1997,3024:1144-1151.[9] Li H, Liu G, Li Y, et al. A robust, efficient, and fast global motion estimation method from MPEG compressed video // IEEE Proc. PCM2002, LNCS 2532, Taiwan:SPIE, 2002: 151-158.[10] Moscheni F, Dufaux F, Kunt M. A new two-stage global/local motion estimation based on a background/foreground segmentation //IEEE Proc. ICASSP95, Detroit, MI:IEEE,1995:2261-2264.[11] Sorwar G, Murshed M, Dooley L. Fast global motion estimation using iterative least-square estimation technique // IEEE Proc. ICICSPCM 2003, Singapore, IEEE, 2003:282-286.[12] 贺玉文,赵黎,钟玉琢,等.快速鲁棒的全局运动估计算法 [J]. 软件学报, 2001,12(8):1220-1228.[13] Press W H, Flannery B P, Teukolsky S A, et al. Numerical recipes in C: The Art of Scientific Computing [M]. Cambridge: Cambridge University Press, 2003: 32-102.

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