Adaptive Video Motion Estimation for Embedded Processors
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Solution Overview
Problem
Traditional block motion compensation methods in video coding require significant computational power and data bandwidth, especially at higher resolutions, due to large search areas and extensive calculations for motion estimation, which is not efficiently managed in embedded processor architectures.
Innovation Solution
Adaptive motion estimation methods that use statistics from prior frames to limit the search range and switch between telescopic and 2-step searches, reducing computational complexity and data bandwidth by predicting motion vector ranges and optimizing search areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional block motion compensation with large search areas is used, then motion estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the motion estimation process into two distinct phases: coarse motion estimation using a reduced search area to obtain initial motion vectors, and fine motion estimation using a larger search area to refine those vectors. This segmentation allows the system to achieve accurate motion estimation while significantly reducing the total computational complexity compared to performing exhaustive search over the entire search area.
Solution Approach 2:
The patent implements preliminary action by performing coarse motion estimation first to obtain initial motion vectors before conducting fine motion estimation. These preliminary motion vectors serve as starting points that guide the subsequent fine estimation process, allowing the system to converge to accurate results more efficiently than starting with a complete exhaustive search.
2Measurement precision
If traditional block motion compensation with large search areas is used, then motion estimation accuracy is improved, but data bandwidth requirement increases
Solution Approach 1:
The patent segments the search area into a reduced region for coarse estimation and a larger region for fine estimation. By processing the reduced search area first, the system reduces the immediate data bandwidth requirement for loading reference pixels, while still achieving accurate motion estimation through the subsequent fine estimation phase that uses the preliminary vectors to guide the expanded search.
Solution Approach 2:
The preliminary coarse estimation phase generates motion vectors that serve as predictors for the fine estimation phase. This preliminary action allows the fine estimation to focus computational resources and data bandwidth on refined searches around the predicted locations, rather than performing exhaustive searches across the entire search area, thereby reducing overall data bandwidth requirements.
3Measurement precision
If exhaustive search is used for motion estimation, then motion vector accuracy is improved, but processing time increases
Solution Approach 1:
The patent divides the exhaustive search into two segmented phases: a coarse phase over a reduced search area that quickly identifies approximate motion vectors, and a fine phase over the full search area that refines these vectors. This segmentation dramatically reduces processing time compared to performing a single exhaustive search, while maintaining motion vector accuracy through the refinement step.
Solution Approach 2:
The coarse motion estimation serves as a preliminary action that provides initial motion vector estimates before the fine estimation phase. This preliminary step eliminates the need to perform exhaustive search from scratch, allowing the system to achieve accurate motion vectors with significantly reduced processing time by guiding the fine search toward the correct region.
4Productivity
If block motion compensation is used, then temporal redundancy removal is improved, but embedded processor efficiency deteriorates
Solution Approach 1:
The patent segments the motion estimation computation into coarse and fine phases that can be efficiently implemented on embedded processors. The coarse phase uses reduced computational requirements suitable for embedded hardware, while the fine phase refines results using the preliminary vectors. This segmentation makes block motion compensation feasible and efficient on embedded processor architectures.
Solution Approach 2:
The preliminary coarse estimation generates motion vectors that serve as predictors for subsequent fine estimation, reducing the computational burden on embedded processors. This preliminary action allows embedded systems to achieve effective temporal redundancy removal through block motion compensation without being overwhelmed by the full computational complexity of exhaustive search.
Data Source
AI summary
Motion estimation in video encoding switches among motion estimation methods for successive predicted pictures depending upon statistics of prior pictures. Locally averaged motion vectors, fraction of intra-coded macroblocks, average quantization parameter, and so forth provide tests for applicability of particular motion estimation methods, such as ones which perform better for large motion or perform better for small motion with complex texture.