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학술지 Design of Efficient Perspective Affine Motion Estimation/Compensation for Versatile Video Coding (VVC) Standard
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최영주, 전동산, 정원식, 김병규
Electronics, v.8 no.9, pp.1-15
19HR2500, [통합과제] 초실감 테라미디어를 위한 AV부호화 및 LF미디어 원천기술 개발, 최진수
The fundamental motion model of the conventional block-based motion compensation in High Efficiency Video Coding (HEVC) is a translational motion model. However, in the real world, the motion of an object exists in the form of combining many kinds of motions. In Versatile Video Coding (VVC), a block-based 4-parameter and 6-parameter affine motion compensation (AMC) is being applied. In natural videos, in the majority of cases, a rigid object moves without any regularity rather than maintains the shape or transform with a certain rate. For this reason, the AMC still has a limit to compute complex motions. Therefore, more flexible motion model is desired for new video coding tool. In this paper, we design a perspective affine motion compensation (PAMC) method which can cope with more complex motions such as shear and shape distortion. The proposed PAMC utilizes perspective and affine motion model. The perspective motion model-based method uses four control point motion vectors (CPMVs) to give degree of freedom to all four corner vertices. Besides, the proposed algorithm is integrated into the AMC structure so that the existing affine mode and the proposed perspective mode can be executed adaptively. Because the block with the perspective motion model is a rectangle without specific feature, the proposed PAMC shows effective encoding performance for the test sequence containing irregular object distortions or dynamic rapid motions in particular. Our proposed algorithm is implemented on VTM 2.0. The experimental results show that the BD-rate reduction of the proposed technique can be achieved up to 0.45% and 0.30% on Y component for random access (RA) and low delay P (LDP) configurations, respectively.
KSP 제안 키워드
AMC structure, Control Points, Degrees of freedom(DOF), Low Delay, Model-based method, Motion Compensation(MoCo), Motion Vector(MV), Motion estimation(ME), Perspective motion model, Random Access, Real-world
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