motion estimation and video compression
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MOTION ESTIMATION AND VIDEO COMPRESSION. By, Jarjit Tandel Waseem Khatri Sidhesh Khapare. Outline. Introduction Motion Estimation - PowerPoint PPT PresentationTRANSCRIPT
MOTION ESTIMATION AND VIDEO COMPRESSION
By,
Jarjit Tandel
Waseem Khatri
Sidhesh Khapare
Outline
Introduction Motion Estimation Motion Compensation Algorithm Block Estimation Algorithm Compression Results Conclusion References
Introduction
Motivation Understand Motion Estimation Reconstruction of Video Using Motion
Compensation
Background A Video sequence consist of series
of frames.
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
What is Motion Compensation
Reconstruction of video file Reference frame is used to predict current frame
using motion vectors.
Proposed Algorithm
Extract frames ‘k’ and ‘k+1’
3-step motion
estimation
Obtain motion vectors
Forward motion
estimation
Predicted video frame
Original frame ‘k+1’
Prediction error
Quantized error
Input Color Video
Predicted video frame
Reconstructed frame ‘k+1’
-
+
++
Proposed Algorithm
Extract frames ‘k’ and ‘k+1’
3-step motion
estimation
Obtain motion vectors
Forward motion
estimation
Predicted video frame
Original frame ‘k+1’
Prediction error
Quantized error
Input Color Video
Predicted video frame
Reconstructed frame ‘k+1’
-
+
++
Three Step Search Method
Input RGB Video
Extract Frames
Select block With lowestMSE/MAD
Divide each Frame into Blocks of
size 16X16
Divide each block into
9 equal parts
Calculate MSE
Select block With lowestMSE/MAD
Divide the selected Block into
9 equal parts
Calculate MSE
Divide the selected
Block into 9 equal parts
Calculate MSE
Select block With lowestMSE/MAD
Draw line connecting Center of frame to this point
Video Frame
16 X 16 Block
Block Representation
Extract frames ‘k’ and ‘k+1’
3-step motion
estimation
Obtain motion vectors
Forward motion
estimation
Predicted video frame
Original frame ‘k+1’
Prediction error
Quantized error
Input Color Video
Predicted video frame
Reconstructed frame ‘k+1’
-
+
++
Predicting Next Frame
Frames ‘k’ and ‘k+1’ Predicted Frame ‘k+1’Motion Vectors
Block Representation
Extract frames ‘k’ and ‘k+1’
3-step motion
estimation
Obtain motion vectors
Forward motion
estimation
Predicted video frame
Original frame ‘k+1’
Prediction error
Quantized error
Input Color Video
Predicted video frame
Reconstructed frame ‘k+1’
-
+
++
Prediction Error Calculation
Frame 60 Frame 61
Prediction error
+
-
Predicted Frame
Results
Forward motion
estimation
3-step motion
estimation
-
+
Quantized error
+
+
Color video Extracted frames ‘k’ and ‘k+1’
Motion Vectors Predicted frame
Predicted frame
Frame ‘k+1’
Prediction errorReconstructed
video frame
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.
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 Hall Signal 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.
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