Global Movement Image Stabilization Decomposition
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Solution Overview
Problem
Existing image stabilization techniques struggle to effectively address global movement in image sequences while preserving local movement, particularly when analyzing minor or small local movements amidst changing device location and angle.
Innovation Solution
A method and system for global movement image stabilization (GMIS) that decomposes complex motion into elementary 2D motion components, calculating global motion group parameters to generate a deformation vector field that removes global motion from sequential frames, utilizing techniques like GLORIA and SOFIA to estimate average global movement without full optical flow calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full optical flow calculations are performed to accurately capture motion between frames, then measurement precision of motion is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent segments the motion field into local motion components and global motion components. By dividing the complex optical flow calculation into separate local and global motion estimation processes, the system achieves accurate motion measurement while reducing overall computational complexity. Local motion is estimated independently in small regions, and global motion is calculated separately, avoiding the need for full-frame optical flow computation.
Solution Approach 2:
The patent extracts and removes the global motion component from the image sequence before performing local motion analysis. By taking out the global motion (translation, rotation, scaling) as a separate step, the system can focus computational resources on estimating only the local motion components, thereby reducing computational complexity while maintaining measurement precision for local movements.
2Stability of the object's composition
If global motion removal is applied to stabilize images, then image stabilization is improved, but local motion information may be lost or distorted
Solution Approach 1:
The patent segments motion into distinct local and global components that are processed separately. Local motion is estimated independently for each region and preserved during stabilization, while only global motion is removed. This segmentation ensures that image stability is improved through global motion removal without losing important local motion information.
Solution Approach 2:
The patent applies different processing treatments to different parts of the image: global motion removal is applied uniformly across the entire frame to achieve stabilization, while local motion estimation and preservation are applied specifically to local regions. This local quality approach ensures that stabilization does not distort or lose local motion information.
3Measurement precision
If complex motion decomposition into multiple elementary components is performed, then motion analysis accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent segments complex motion into elementary 2D motion components (translation in x and y directions, rotation, scaling). By decomposing motion into these fundamental components that can be estimated independently and combined, the system achieves high motion analysis accuracy while reducing processing time compared to estimating complex motion patterns directly.
Solution Approach 2:
The patent changes the parameter representation of motion from complex, coupled motion fields to independent elementary motion parameters (translation vectors, rotation angles, scaling factors). This parameter transformation allows each component to be estimated separately using simpler algorithms, improving computational efficiency while maintaining motion analysis accuracy through the combination of elementary components.
Data Source
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AI summary
A method of global movement image stabilization may include calculating a global motion group parameter with respect to first and second sequential frames for two or more elementary 2D motion components of a motion group. Each global motion group parameter may be applied to a motion group vector field that corresponds to the elementary 2D motion component to which the respective global motion group parameter applies to generate a global motion group vector field corresponding to each elementary 2D motion component of the motion group. The global motion group vector fields may be summed pointwise to generate a global motion deformation vector field that provides global motion from the second frame to the first frame. The global deformation vector field may be cumulated with a previous cumulative global deformation vector field that provides global movement from the first frame to one or more previous frames to generate a current cumulative global motion deformation vector field. The second frame may be deformed by the current cumulative global motion deformation vector field to generate a stabilized frame having global movement removed.