Dynamic Image Stabilization Path via Dynamic Programming
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Solution Overview
Problem
Existing image stabilization methods for user-wearable devices are not optimal, particularly when dealing with dramatic device motion, as they often compromise between attenuating high-frequency motion and achieving a suitable step response.
Innovation Solution
A method and apparatus that stabilize image sequences by defining boundary conditions for a stabilization band and deriving a stabilization path within this band using captured image data, allowing for optimal compensation of unintentional device motion while preserving intentional motion, employing a processor and dynamic programming algorithms to determine the optimal stabilization path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional stabilization methods are applied to user-wearable devices with dramatic motion, then high-frequency motion can be attenuated, but the step response deteriorates and motion compensation becomes suboptimal
Solution Approach 1:
The patent applies dynamics by making the stabilization path adaptive rather than fixed. The method derives a stabilization path that dynamically adjusts to the actual device motion characteristics, allowing the system to optimize between attenuation precision and step response speed based on real-time motion conditions. This is achieved through formulating an optimization problem that finds the best path within a stabilization band according to specific criteria.
Solution Approach 2:
The patent changes parameters by introducing a stabilization band with boundary conditions and deriving an optimal path within this band. Instead of using fixed stabilization parameters, the system adjusts the stabilization path parameters based on the actual device motion and captured image data, optimizing the balance between motion attenuation and response speed through parameter optimization.
2Measurement precision
If aggressive stabilization is applied to reduce noisy image data, then motion noise is attenuated, but image clipping and distortion increase
Solution Approach 1:
The patent applies preliminary action by defining boundary conditions and a stabilization band before deriving the optimal path. This preliminary framework constrains the stabilization process to operate within acceptable geometric limits, preventing excessive correction that would cause clipping or distortion while still achieving effective noise reduction within the defined boundaries.
Solution Approach 2:
The patent uses feedback by utilizing captured image data disposed within the stabilization band to derive the stabilization path. The system continuously monitors the actual device motion through captured images and adjusts the stabilization path accordingly, providing feedback-based optimization that balances noise reduction with geometric accuracy.
3Device complexity
If traditional filtering methods are used for stabilization, then processing is simpler, but the ability to preserve intentional motion while removing unintentional motion deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the stabilization problem into distinct components: defining boundary conditions, establishing a stabilization band, and deriving an optimal path within that band. This segmentation allows the system to handle different aspects of motion compensation separately, improving the ability to distinguish between intentional and unintentional motion while maintaining manageable processing complexity.
Data Source
AI summary
A video stabilization scheme which uses a dynamic programming algorithm in order to determine a best path through a notional stabilization band defined in terms of a trajectory of an image capture element. The best path is used in order to produce an optimally stabilized video sequence within the bounds defined by the image capture area of the image capture element.