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MOTION ESTIMATION AND VIDEO COMPRESSION

MOTION ESTIMATION AND VIDEO COMPRESSION. By, Jarjit Tandel Waseem Khatri Sidhesh Khapare. Outline. Introduction Motion Estimation

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MOTION ESTIMATION AND VIDEO COMPRESSION

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  1. MOTION ESTIMATION AND VIDEO COMPRESSION By, Jarjit Tandel Waseem Khatri Sidhesh Khapare

  2. Outline • Introduction • Motion Estimation • Motion Compensation • Algorithm • Block Estimation Algorithm • Compression • Results • Conclusion • References

  3. Introduction • Motivation • Understand Motion Estimation • Reconstruction of Video Using Motion Compensation • Background • A Video sequence consist of series of frames.

  4. What is Motion Estimation • Predict current frame from previous frame • Determine the displacement of an object in the video sequence • Types of Motion Estimation: • Horn and Schunck • Three Step Search Block Motion Method • Hierarchical Block Motion

  5. What is Motion Compensation • Reconstruction of video file • Reference frame is used to predict current frame using motion vectors.

  6. Proposed Algorithm Input Color Video Extract frames ‘k’ and ‘k+1’ 3-step motion estimation Obtain motion vectors Forward motion estimation Predicted video frame - Predicted video frame Original frame ‘k+1’ + + + Quantized error Prediction error Reconstructed frame ‘k+1’

  7. Proposed Algorithm Input Color Video Extract frames ‘k’ and ‘k+1’ 3-step motion estimation Obtain motion vectors Forward motion estimation Predicted video frame - Predicted video frame Original frame ‘k+1’ + + + Quantized error Prediction error Reconstructed frame ‘k+1’

  8. Three Step Search Method Input RGB Video Extract Frames Divide each Frame into Blocks of size 16X16 Divide each block into 9 equal parts Calculate MSE Select block With lowest MSE/MAD Divide the selected Block into 9 equal parts Video Frame Draw line connecting Center of frame to this point Select block With lowest MSE/MAD Calculate MSE Divide the selected Block into 9 equal parts Select block With lowest MSE/MAD Calculate MSE 16 X 16 Block

  9. Block Representation Input Color Video Extract frames ‘k’ and ‘k+1’ 3-step motion estimation Obtain motion vectors Forward motion estimation Predicted video frame - Predicted video frame Original frame ‘k+1’ + + + Quantized error Prediction error Reconstructed frame ‘k+1’

  10. Predicting Next Frame Frames ‘k’ and ‘k+1’ Motion Vectors Predicted Frame ‘k+1’

  11. Block Representation Input Color Video Extract frames ‘k’ and ‘k+1’ 3-step motion estimation Obtain motion vectors Forward motion estimation Predicted video frame - Predicted video frame Original frame ‘k+1’ + + + Quantized error Prediction error Reconstructed frame ‘k+1’

  12. Frame 60 Frame 61 + - Prediction error Predicted Frame Prediction Error Calculation

  13. Results 3-step motion estimation Forward motion estimation Motion Vectors Predicted frame Color video Extracted frames ‘k’ and ‘k+1’ - + Predicted frame Frame ‘k+1’ + + Quantized error Reconstructed video frame Prediction error

  14. Conclusion • Advantages: • Simplicity: Simple geometric transformation of pixel co-ordinate. • Easy to implement in hardware Limitations: • Fails for zoom, rotational motion, and under local deformations.

  15. References [1] H. Gharavi and M. Mills, “Block-matching motion estimation algorithms: New results,” IEEE Trans. Circ. and Syst., vol. 37, pp. 649-651, 1990. [2] V. Seferidis and M. Ghanbari, “General approach to block-matching motion estimation,” Optical Engineering, vol. 32, pp. 1464-1474, July 1993. [3] M. Bierling, “Displacement estimation by hierarchical block-matching,” Proc. Visual Comm. and Image Proc., SPIE vol. 1001, pp. 942-951, 1988. [4] B. K. P. Horn and B. G. Schunck, “Determining Optical Flow,” Artif. Intell., vol. 17, pp. 185-203, 1981. [5] S. V. Fogel, “Estimation of velocity vector fields from time varying image sequences,” CVGIP: Image Understanding, vol. 53, pp. 253-287, 1991. [6] T. S. Huang, ed., Image Sequence Analysis, Springer Verlag, 1981. [7] A. V. Oppenheim and R. W. Schafer, “Discrete - Time Signal Processing,” Prentice Hall Signal Processing Series, 1989. [8] A. M. Tekalp, “Digital Video Processing,” Prentice HallSignal Processing Series, 1995. [9] D. E. Dudgeon, “Multidimensional Digital Signal Processing,” Prentice Hall Signal Processing Series, 1996. [10] K. Sayood, “Introduction to Data Compression,” Morgan Kaufmann Publishers, 2006.

  16. Thank You

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