Motion Estimation Segmentation for Video Encoder Complexity
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Solution Overview
Problem
The complexity of motion estimation in video encoding, particularly in the H.264 standard, becomes difficult due to the numerous ways to partition a picture, leading to optimization challenges given hardware constraints.
Innovation Solution
A system and method for motion estimation in video encoders that includes a coarse motion estimator and a fine motion estimator, using decimation and refinement engines to efficiently determine motion vectors and prediction modes, optimizing the partitioning process for improved performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of ways to partition a picture is increased, then motion estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The motion estimation process is segmented into two distinct stages: coarse motion estimation and fine motion estimation. The coarse stage handles the majority of partitioning options to establish initial motion vectors, while the fine stage refines only the most promising candidates. This segmentation reduces the computational burden at each stage while maintaining overall accuracy.
Solution Approach 2:
The coarse motion estimation performs preliminary action by establishing initial motion vectors and identifying promising partitioning options before the fine motion estimation stage. This preliminary work filters out unlikely candidates, allowing the fine stage to focus computational resources on refining only the most relevant motion vectors rather than exhaustively searching all partitions.
2Measurement precision
If exhaustive search of motion vectors is performed, then motion vector accuracy is improved, but processing time increases
Solution Approach 1:
The exhaustive search process is segmented into two phases: a coarse phase that evaluates many partitioning options quickly to establish initial motion vectors, and a fine phase that performs more accurate but limited search only on promising candidates. This segmentation maintains accuracy for critical motion vectors while reducing overall processing time.
Solution Approach 2:
The system performs partial exhaustive search rather than complete exhaustive search. The coarse motion estimation evaluates more partitioning options than would be practical in a single fine stage, establishing a broad set of candidates. The fine stage then performs a more limited but accurate search only on the most promising candidates, achieving sufficient accuracy without the full computational cost of exhaustive search.
3Ease of manufacture
If motion estimation is optimized for hardware constraints, then implementation feasibility is improved, but optimization difficulty increases
Solution Approach 1:
The motion estimation algorithm is segmented into coarse and fine stages with distinct computational characteristics. The coarse stage uses simpler, more hardware-friendly operations to establish initial vectors, while the fine stage applies more complex but accurate refinement only where necessary. This segmentation makes the overall system more implementable on hardware with limited resources.
Solution Approach 2:
The system dynamically adjusts the balance between coarse and fine estimation based on the specific requirements of each macroblock or picture region. The fine motion estimation is applied selectively only to regions where higher accuracy is needed, rather than uniformly across the entire image. This dynamic approach optimizes hardware utilization and reduces overall computational burden.
Data Source
AI summary
Described herein is a method and system for motion estimation in a video encoder. There are two parts to the motion estimation. Coarse motion estimation generates a set of motion vectors for a current picture and at least one reference picture. Typically, coarse motion estimation operates on sub-sampled pictures. Fine motion estimation can refine coarse motion estimation results by searching interpolated video data in a region defined by the motion vectors from the coarse motion estimation.