Video Stabilization via Relative View Direction Compensation
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Solution Overview
Problem
Conventional video stabilization technologies face challenges in accurately compensating for camera movement and shaking, with 2D analysis methods failing to correctly model 3D motion and 3D analysis methods causing image distortion due to high computational requirements.
Innovation Solution
A video stabilization method that measures inter-frame camera motion based on relative view direction differences, generates a camera motion path, and adjusts the camera view direction to align with a user's predicted view direction, reducing computational complexity while minimizing image distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If 2D motion model is used for video stabilization, then computation amount is reduced, but 3D motion cannot be correctly modeled
Solution Approach 1:
The patent transitions from 2D motion analysis to 3D motion analysis by reconstructing three-dimensional space information and camera position information from two-dimensional image sequences. This dimensional upgrade enables correct modeling of 3D motion while maintaining computational feasibility through efficient reconstruction algorithms.
Solution Approach 2:
The patent creates a virtual 3D model (copy) of the real-world scene and camera motion path. By working with this reconstructed 3D model rather than directly processing complex real-world 3D data, the system achieves accurate motion modeling with reduced computational requirements.
2Manufacturing precision
If 3D motion structure analysis is used for video stabilization, then correct video stabilization is achieved, but image distortion occurs in partial areas
Solution Approach 1:
The patent applies different processing strategies to different regions of the image. By identifying partial areas prone to distortion and applying localized correction techniques, the system maintains high stabilization accuracy in critical regions while minimizing distortion in other areas.
Solution Approach 2:
The patent performs preliminary analysis to identify potential distortion areas before they occur, and applies pre-compensation measures. By predicting where distortion might occur based on camera motion patterns and applying corrective transformations in advance, the system prevents distortion rather than correcting it afterward.
3Manufacturing precision
If 3D motion structure analysis is used for video stabilization, then correct video stabilization is achieved, but computational requirements increase considerably
Solution Approach 1:
The patent performs preliminary reconstruction of 3D space information and camera position information from the image sequence before applying stabilization transformations. By preparing the 3D model in advance and caching intermediate results, the system reduces the computational burden during the actual stabilization process.
Solution Approach 2:
The patent employs dynamic algorithms that adapt the level of 3D reconstruction detail based on the complexity of the scene and camera motion. In simpler scenarios, the system uses simplified 3D models with fewer computational requirements, while reserving full 3D reconstruction for complex scenarios that demand higher accuracy.
Data Source
AI summary
A video stabilization method includes: measuring an inter-frame camera motion based on a difference angle of a relative camera view direction in comparison with a reference camera view direction in each frame of a frame sequence of a video; generating a camera motion path of the frame sequence by using the inter-frame camera motion and determining a camera view direction adjustment angle based on a user's view direction by using the camera motion path; and compensating for the camera view direction by using the camera view direction adjustment angle in each frame.