1. LI Hong-ye, LIU Ming-jun, ZHANG Zhi-qiang MINES 2009 1

2. 2 Humaira Nisar and Tae-Sun Choi, Senior Member, IEEE ICIP 2009

3. Introduction Introduction to UMHexagonS New Fast Motion Estimation Algorithm Simulation Introduction to Fractional Motion Estimation Fractional Pixel Error Surface Quadrant Based Directional Fractional Pixel ME Algorithm Simulation Conclusion 3

4. Motion estimation(ME) is time consuming. Many fast motion estimation algorithms which have been proposed still can’t satisfy the real-time application. ME consists of two stages: Integer pixel ME Fractional pixel ME Generally Integer pixel ME takes most of computational time of the whole ME. Due to the development of fast ME algorithm, computational cost of integer pixel has been greatly reduced. Fractional ME has strong impact on PSNR, and has complex sub pel interpolation process. 4

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6. Combine many strategies together and achieve both fast speed and high accuracy. Performs well both in small motion sequences and large motion sequences. Adaptively adopt different searching pattern according to SAD and have early termination strategy to reduce searching time. Only 10% complexity compare with Full Search algorithm. Adapted in H.264 reference software. 6 [10] Zhibo Chen, Jianfeng Xu, Yun He, and Junli Zheng, “Fast integer-pel and fractional-pel motion estimation for H.264/AVC,”Journal of Visual Communication & Image Representation, April 2006, pp. 264-290.

7. 7 (0) (1) (2) (3) (4-1) (4-2) ` ` Step1: Unsymmetrical-cross search Step2: Small rectangular full search Step3: Uneven multi-hexagon-grid search Step4: Extended hexagons-based search

8. Ameliorates UMHexagonS algorithm to reduce search point on three aspects: 8 Proposed algorithmUMHexagonS algorithm New square patternStep2: Small rectangular full search Multi-octagon-gird searchStep3: Uneven multi-hexagon-grid search Add Horizontal and vertical hexagonStep4: Extended hexagons-based replace

9. 5x5 full search  3x3 By studying the distribution of MV 80% in 5x5 grid region 70% in 3x3 grid region Replace reason 80%  70% 5x5=25  3x3=9 36% 9

10. Hexagon(6)  Octagon(8) Replace reason Octagon has more edges than hexagon and closing to circle 16 points  8 points 50% 10

11. Add horizontal and vertical hexagons Add reason Orientation bias 11 Uniform Horizontal Vertical Search patternAdopt pattern 16x16, 8x8Uniform hexagon 16x8, 8x4Horizontal hexagon 8x16, 4x8Vertical hexagon 4x4Go to step 4-2

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13. HFPS: 17 pointsCBFPS 13 [2] Z. Chen, P. Zhou, Y. He and Y. Chen, “Fast Integer Pel and Fractional Pel Motion Estimation for JVT” ITU-T, Doc. #JVT-F-017, Dec. 2002.”

14. Error surface of fractional-pel motion estimation (1/8-pel case) Unimodal error surface Redundant to check opposite direction points Error surface of integer-pel motion estimation (search range = 32) Drop into local minimum 14

15. 15 ConditionQuadrant selection Approach Quadrant I Quadrant II Quadrant III Quadrant IV

16. 16 Half pel points: Step1: Calculate the cost of the best integer-pel position and 2 search points. Step2: Use quadrant selection approach selects quadrant, and selects additional ½ pel points. Case1: For quadrant I, only one additional ½ pel point is selected. Case2: For quadrant II, two additional ½ pel points are selected. Case3: For quadrant III, three additional ½ pel points are selected. Case4: For quadrant IV, two additional ½ pel points are selected. Choose the best ½ pel point for search ¼ pel start point. I IIIII IV

17. 17 Quarter pel points: search procedure is the same as ½ pel points. At most : 11 points I I IIIII IV II

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21. New fast motion estimation algorithm based on H.264 improves on the UMHexagonS in three aspects. Reduce 30%~40% computational complexity of UMHexagonS without accuracy loss. Efficient for real time video coding applications. Fast fractional search motion estimation algorithm based on uni- modal error surface assumption divides search range into four quadrants and finds the minimum error points by searching only some points that lie in that quadrant. Reduce computation time and keep almost same performance as CBFPS algorithm. 21