1. BLOCK BASED MOTION ESTIMATION

2. Road Map Block Based Motion Estimation Algorithms. Procedure Of 3-Step Search Algorithm. 4-Step Search Algorithm. N-Step search algorithm. 2D-Logarithmic Search (2D-LOG): Why ? Advantage and Disadvantage of 2-Dlog Algorithm. The Orthogonal search algorithm(OSA).

3. Road Map One At A Time Search Algorithm. Mesh Based Motion Estimation. Multiple Choice Question(MCQ).

4. Block Based Motion Estimation Algorithms These algorithms estimate the amount of motion on a block by block basis. i.e. for each block in the current frame, a block from the previous frame is found, that is said to match this block based on a certain criterion. Block based motion prediction includes following steps 1.Breaking image up into non overlapping square blocks(M). 2.Estimate translation for each block. 3.Use this to predict next frame, code difference (MPEG-2).

5. Procedure Of 3-Step Search Algorithm There are following procedure of 3-step search algorithm Step 1: 1.Totally (3+5)8+9=17 points are checked including the central nine point on the 3*3 grid. 2.If the minimum BDM point is the search window center, the search will be stop or terminated; otherwise go to step 2step 2

6. Procedure Of 3-Step Search Algorithm Step 2: if one of center eight neighboring point on the 3*3 grid is found to be minimum in the first step, Go to step 3; otherwise go to step 4step 4 Step 3: move the small 3*3 search window so that the window center is the winning point found in step 1.

7. Procedure Of 3-Step Search Algorithm

8. Cont…

9. 3-Step Search Algorithm

11. 3-Step Search algorithm: Example

12. 4-Step Search Algorithm Advantage: 1.Very Low complexity in terms of selected candidate locations 2.More accurate than three-step search 3.Memory bandwidth saving 4.For small motions, fewer steps calculation are needed Disadvantage: 1.Risk of local minima if motion is far away from center

13. N-Step search algorithm

14. 2D-Logarithmic Search (2D-LOG) Why 2D-logarithmic Search is required? If we wish to calculate the sub pixel( when display device is not able to full size colored image due to some reason so pixel grid color is into single color in rectangular form) accuracy in motion estimation based on block. It requires some additional steps included into the available 3-step search algorithm. Note: The search frame needs to be included to evaluated the criterion function at sub pixel location.

15. 2D-Logarithmic Search (2DLOG) 2D-logarithmic search (2DLOG) is proposed by Jain et. al. in 1981. It uses a (+) cross search pattern in each step. The initial step size is [d/4]. The step size is reduced by half only when the minimum BDM(body distortion measure) point of previous step is the center one or the current minimum point reaches the search window boundary.

16. Cont… Otherwise, the step size remains the same. When the step size reduced to 1. All the 8 checking points adjacent to the center checking point of that step are searched. Two different search paths are shown. The top search path requires (5 +3 +3 +8) = 19 checking points. The lower-right search path requires (5+3+2+3+2+8) =23 checking points.

17. 2-D Logarithmic Algorithm

18. 2-D Log Algorithm

19. Advantage and Disadvantage of 2-Dlog Algorithm Advantage: It is suitable for sequences with fast motion Disadvantage The accuracy of algorithm is low when the motion vector is at an angle to x-y axis.

20. The Orthogonal search algorithm(OSA) The orthogonal search algorithm (OSA) is invented by A. Puri et. al. in 1987. It consists of pairs of horizontal and vertical steps with a logarithmic decreasing in step size. The initial step size is f(d/2) where it is the lower integer truncation function. The search paths of OSA are shown in starting from the horizontal searching step. there are three checking points in the horizontal direction are searched.

21. Cont… The minimum checking point then becomes the center of the vertical searching step, which also consists of three checking points. Then step size decreases by(1/2) half and using the same searching strategy. The algorithm ended with step size equals to one

22. The Orthogonal search algorithm(OSA) There are following cases for checking point: Case 1: For d = 7, the OSA algorithm requires a total of (3 + 2 + 2 +2 + 2 +2)=13 checking points. Case 2: For the general case, the OSA algorithm requires (1 + 4 log2(d + 1) ) checking points.

23. Advantage and Disadvantage of OSA Advantage: Very quick for small motions Disadvantage: Local minima may stop the search very soon

24. One At A Time Search Algorithm

25. One at a time Algorithm Advantage: The procedure can be stopped at any step to ensure low computational cost Disadvantage: Local minima may stop the search very soon

26. Mesh Based Motion Estimation The use of mesh-based prediction provides an alternative approach to the estimation of motion. The procedure is to divide the current frame into a number of patches in either triangular or rectangular shape. Find the best matching corresponding patch in the reference frame when deformed by affine transformation.

27. Mesh Based Motion Estimation The mean absolute difference is commonly used as the matching criterion, and the motion is defined by the change in position of the corresponding vertices. Compared to the conventional block-matching algorithm (BMA), mesh-based motion models provide more visually acceptable results in the predicted frame.

28. Mesh Based Motion Estimation It basically relies on a hexagon formed by seven grid points as shown in Fig. 1. By fixing the position of the six peripheral vertices, the central grid point, G z, is allowed to acquire an optimal motion displacement within the hexagon,

29. Mesh Based Motion Estimation Fig.1 Search for the hexagon matching algorithm. 1.Fix the position of the six vertices Ga to Gf 2.Search for the best position of Gz.

31. References 1.M. Tekalp, "digital video processing" prentice hall, 1995, ISBN 0-13- 190075-7. 2.Yaowang, joern ostermann,ya-qinzhang,"video processing and communications", prentice hall, ISBN 0-13-017547-1,2002. 3.Songtaohuang“ algorithms for motion estimation,” m.Scthesis, univ. Of windsor, 2002.

32. References 4.C. Stiller, J. Konrad, “estimating motion in image sequences,”ieee signal proc. Magazine, vol. 16, issue 4, pp 70-91, 1999. 5. Yui-Lam Chan, Wan-Chi Siu, “An Efficient Search Strategy for Block Motion Estimation Using Image Features” IEEE trans. on Image Proc., Vol. 10, No. 8, 2001. 6.Http://www.di.unipi.it/~lonetti/PhDCourse/ME/An%20Efficient%20Three- Step%20Search%20Algorithm.pdf