Video Stabilization Using Gyro-Feedback Feature Tracking
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Solution Overview
Problem
Pan-tilt-zoom (PTZ) cameras used in surveillance systems often produce blurred videos due to unintended camera shaking or rotation, which existing technologies fail to effectively stabilize.
Innovation Solution
A method and apparatus that detect feature points in video frames, predict their location based on angular velocity from a gyro sensor, and update parameters to correct for image motion, thereby stabilizing the video by removing unwanted camera movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If PTZ camera is used to cover large area with panning and tilting operations, then surveillance coverage is improved, but video stability deteriorates due to camera shaking and rotation
Solution Approach 1:
The system uses gyro sensors to detect camera shaking and rotation in real-time, then feeds this information back to calculate compensation values. These compensation values are applied to adjust the captured images, creating a closed-loop feedback system that continuously counteracts camera movement to maintain video stability while preserving wide-area surveillance capability
Solution Approach 2:
The system dynamically changes parameters including compensation values, search ranges for feature points, and verification thresholds based on detected camera movement characteristics. By adapting these parameters in real-time according to the severity and type of camera shaking, the system maintains stable video output across varying surveillance conditions without sacrificing coverage area
2Measurement precision
If feature point prediction is performed with wide search range to handle large camera movement, then tracking accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary prediction of feature point locations using gyro sensor data before actually searching for the feature points in the current frame. This preliminary action provides an initial estimate that narrows the search range, allowing the system to achieve accurate tracking without performing exhaustive searches across the entire image, thus reducing processing time while maintaining tracking accuracy
Solution Approach 2:
The system dynamically adjusts the search range for feature points based on predicted camera movement from gyro sensors. When camera movement is small, the search range is narrowed to reduce processing; when movement is large, the search range expands to maintain tracking accuracy. This dynamic adaptation allows the system to optimize processing time while preserving tracking precision under varying motion conditions
3Speed
If parameter update is performed frequently to track fast moving feature points, then tracking responsiveness is improved, but measurement accuracy deteriorates due to noise
Solution Approach 1:
The system performs parameter updates at periodic intervals rather than continuously for every frame. This periodic updating reduces the impact of noise and measurement errors while maintaining adequate tracking responsiveness. The system balances the update frequency to ensure that parameter changes are smooth and stable, avoiding excessive responsiveness to noisy measurements while still tracking feature points effectively
Solution Approach 2:
The system applies verification mechanisms and smoothing operations to parameter updates to cushion against noise before parameters are actually changed. By preparing and validating parameter changes in advance through verification steps, the system prevents noisy measurements from causing inaccurate parameter updates, thus maintaining measurement precision while preserving necessary tracking responsiveness
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively stabilizes videos captured by rotatable cameras by accurately predicting and correcting for image motion, improving viewability and reducing camera-induced blur.
Implementation Method 1
acquiring the angular velocity of the camera sensed by a gyro sensor
Data Source
AI summary
A method of stabilizing a video is provided. The method includes detecting a feature point from a first frame; predicting a location of the feature point in a second frame based on a location of the feature point in the first frame and a predetermined parameter; detecting the feature point from the second frame; determining a distance between the predicted location and a location of the feature point detected from the second frame; and updating the parameter based on a location difference between the feature point detected in the first frame and the feature point detected in the second frame, in response to determining that the distance is within a predetermined threshold.