Abstract
Video stabilization is essential for long-range electro-optical systems, especially in situations when the field of view is narrow, since the system shake may produce highly deteriorating effects. It is important that the stabilization works for different camera types, i.e., different parts of the electromagnetic spectrum independently of the weather conditions and any form of image distortion. In this paper, we propose a method for real-time video stabilization that uses only gyroscope measurements, analyze its performance, and implement and validate it on a real-world professional electro-optical system developed at Vlatacom Institute. Camera movements are modeled with 3D rotations obtained by integration of MEMS gyroscope measurements. The 3D orientation estimation quality depends on the gyroscope characteristics; we provide a detailed discussion on the criteria for gyroscope selection in terms of the sensitivity, measurement noise, and drift stability. Furthermore, we propose a method for improving the unwanted motion estimation quality using interpolation in the quaternion domain. We also propose practical solutions for eliminating disturbances originating from gyro bias instability and noise. In order to evaluate the quality of our solution, we compared the performance of our implementation with two feature-based digital stabilization methods. The general advantage of the proposed methods is its drastically lower computational complexity; hence, it can be implemented for a low price independent of the used electro-optical sensor system.
Highlights
This article is an open access articleThe use of video acquisition devices has increased dramatically in the last ten years.Video cameras have become popular in the consumer sphere as well as in industrial and military applications
Since stabilization needs to be independent of observing scenes, weather conditions and image distortions, in our work, we focus on a method based on gyroscope measureand image distortions, in our work, we focus on a method based on gyroscope measurements
We initially decided to use gyroscope FXAS21002 because we found that the solution integrated on a printed circuit board (PCB) is the best choice for testing
Summary
The use of video acquisition devices has increased dramatically in the last ten years. Gyroscope video stabilization is typically accomplished in three stages [10]: Frame to frame estimation of camera orientation change based on gyroscope measurements; 1. 3. Transformation (homography) of the recorded frames based on the estimated unFigure 2 illustrates gyroscope video stabilization. The conclusion is provided in the last secwe present the experimental results with a performance comparison with Google and RFEL feature-based digital stabilization algorithms as well as advantages and disadvantages of the proposed stabilization.
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