Fast gradient methods based on global motion estimation for video compression

This paper presents a fast global motion estimation (GME) algorithm based on gradient methods (GM), which can be used for real-time applications, such as in MPEG4 video compression. This approach improves the existing state-of-the-art GME algorithms by introducing two major modifications: first, only a small subset (down to 3%) of the original image pixels is used in the estimation process. Second, an interpolation-free formulation of the basic GM is derived, further decreasing the computational complexity. Experimental results show no loss of GME accuracy and compression efficiency compared to the MPEG-4 verification model, while reducing the computational complexity of the GME by a factor of 20.

[1]  Aljoscha Smolic,et al.  High-resolution video mosaicing , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[2]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[3]  Thomas Wiegand,et al.  Using multiple global motion models for improved block-based video coding , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[4]  Thomas Sikora,et al.  The MPEG-4 video standard verification model , 1997, IEEE Trans. Circuits Syst. Video Technol..

[5]  A. Murat Tekalp,et al.  Digital Video Processing , 1995 .

[6]  Larry S. Davis,et al.  Developing Real-Time Computer Vision Applications for Intel Pentium III based Windows NT Workstations , 1999 .

[7]  Michal Irani,et al.  Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency , 1993, J. Vis. Commun. Image Represent..

[8]  Frédéric Dufaux,et al.  Efficient, robust, and fast global motion estimation for video coding , 2000, IEEE Trans. Image Process..

[9]  P. Anandan,et al.  Mosaic based representations of video sequences and their applications , 1995, Proceedings of IEEE International Conference on Computer Vision.

[10]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[11]  Michal Irani,et al.  Computing occluding and transparent motions , 1994, International Journal of Computer Vision.

[12]  David J. Fleet,et al.  Performance of optical flow techniques , 1994, International Journal of Computer Vision.

[13]  Nikolaos Grammalidis,et al.  Sprite generation and coding in multiview image sequences , 2000, IEEE Trans. Circuits Syst. Video Technol..

[14]  Aljoscha Smolic,et al.  Long-term global motion estimation and its application for sprite coding, content description, and segmentation , 1999, IEEE Trans. Circuits Syst. Video Technol..

[15]  Harpreet S. Sawhney,et al.  Compact Representations of Videos Through Dominant and Multiple Motion Estimation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Yuzhuo Zhong,et al.  A pre-analysis method for robust global motion estimation , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[17]  Richard Szeliski,et al.  Video mosaics for virtual environments , 1996, IEEE Computer Graphics and Applications.