Preview Image Stabilization for High-Magnification Object Tracking
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Solution Overview
Problem
Existing image stabilization methods in electronic devices fail to effectively stabilize images during high-magnification photography, particularly distinguishing between intentional and unintentional device movements, leading to suboptimal stabilization performance and unwanted stabilization strength.
Innovation Solution
An electronic device with a processor configured to detect objects in a preview image at high magnification and adjust image stabilization strength based on object detection, using trigger events to increase or decrease stabilization as needed, thereby providing targeted stabilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If digital zoom is applied to provide high-magnification images, then zoom magnification increases, but image stabilization performance deteriorates due to increased preview image motion
Solution Approach 1:
The system dynamically adjusts the image stabilization parameter based on detected object characteristics and motion patterns. The stabilization strength is not fixed but adapts in real-time according to whether the motion is intentional (user changing FOV) or unintentional (shake), allowing effective stabilization even at high zoom magnifications where traditional fixed-parameter methods fail
Solution Approach 2:
The invention changes the image stabilization parameter value based on detection results. When an object is detected and intentional motion is identified, the stabilization parameter is adjusted to provide appropriate stabilization strength, thereby improving image stabilization performance across different zoom magnification levels without sacrificing the ability to capture intentional FOV changes
2Stability of the object's composition
If image stabilization is applied with fixed strength, then stabilization is consistently applied, but it cannot distinguish between intentional user movement to change FOV and unintentional shake
Solution Approach 1:
The system uses feedback from object detection and motion analysis to continuously adjust the image stabilization parameter. By monitoring whether an object remains within a specified area over time and analyzing motion patterns, the system receives feedback about whether motion is intentional or unintentional, and adjusts stabilization strength accordingly, achieving both consistency and adaptability
Solution Approach 2:
The image stabilization system serves itself by automatically detecting motion types and adjusting its own parameter without user intervention. The system self-regulates the stabilization strength based on detected object characteristics and motion patterns, eliminating the need for manual user input while achieving adaptive stabilization
3Measurement precision
If object detection is performed in high-magnification preview images, then targeted stabilization can be achieved, but device complexity increases
Solution Approach 1:
The system segments the preview image into a grid of specified areas and performs object detection by checking whether objects are present within these areas. This segmentation approach allows precise object detection and tracking without requiring complex full-image analysis, thereby achieving high measurement precision while controlling device complexity through divided processing regions
Data Source
AI summary
An electronic device includes: a camera; a display; and at least one processor electrically connected to the camera and the display. The at least one processor is configured to: obtain an image data from the camera; output a preview image of the image data on the display, based on a configured magnification; detect at least one object of the preview image in a state in which the configured magnification is greater than a reference magnification; and perform an image stabilization on the preview image, based on the detected at least one object of the preview image.