video stabilization
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2022 ◽  
pp. 1-1
Author(s):  
Chen Li ◽  
Li Song ◽  
Shuai Chen ◽  
Rong Xie ◽  
Wenjun Zhang

Author(s):  
Semiha Dervişoğlu ◽  
Mehmet Sarıgül ◽  
Levent Karacan

Video stabilization is the process of eliminating unwanted camera movements and shaking in a recorded video. Recently, learning-based video stabilization methods have become very popular. Supervised learning-based approaches need labeled data. For the video stabilization problem, recording both stable and unstable versions of the same video is quite troublesome and requires special hardware. In order to overcome this situation, learning-based interpolation methods that do not need such data have been proposed. In this paper, we review recent learning-based interpolation methods for video stabilization and discuss the shortcomings and potential improvements of them.


2021 ◽  
Author(s):  
Chenyi Yang ◽  
Yuqing He ◽  
Danfeng Zhang

2021 ◽  
Vol 30 (6) ◽  
pp. 1103-1110
Author(s):  
CHENG Keyang ◽  
LI Shichao ◽  
RONG Lan ◽  
WANG Wenshan ◽  
SHI Wenxi ◽  
...  

Author(s):  
Gijs M. W. Reichert ◽  
Marcos Pieras ◽  
Ricardo Marroquim ◽  
Anna Vilanova

AbstractOne common way to aid coaching and seek to improve athletes’ performance is by recording training sessions for posterior analysis. In the case of sailing, coaches record videos from another boat, but usually rely on handheld devices, which may lead to issues with the footage and missing important moments. On the other hand, by autonomously recording the entire session with a fixed camera, the analysis becomes challenging owing to the length of the video and possible stabilization issues. In this work, we aim to facilitate the analysis of such full-session videos by automatically extracting maneuvers and providing a visualization framework to readily locate interesting moments. Moreover, we address issues related to image stability. Finally, an evaluation of the framework points to the benefits of video stabilization in this scenario and an appropriate accuracy of the maneuver detection method.


2021 ◽  
Author(s):  
Yu-Ta Chen ◽  
Kuan-Wei Tseng ◽  
Yao-Chih Lee ◽  
Chun-Yu Chen ◽  
Yi-Ping Hung

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6219
Author(s):  
Petar D. Milanović ◽  
Ilija V. Popadić ◽  
Branko D. Kovačević

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.


2021 ◽  
Author(s):  
Yosuke Takeo ◽  
Takeshi Sekiguchi ◽  
Shinji Mitani ◽  
Tadahito Mizutani ◽  
Yoji Shirasawa ◽  
...  

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