Motion intention optimization for multirotor robust video stabilization

Aguilar, Wilbert G.; Ángulo, Cecilio; Pardo, Jorge A.

doi:10.1109/chilecon.2017.8229689

Cited by 1 publication

(1 citation statement)

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“…After smoothing the trajectory using the Kalman filter, it is used as a baseline to deform multiple original trajectories [10] and create new paths. Since this paper aims to address video shake in multi-camera settings [11] , it is necessary to consider the correlation between adjacent cameras. Therefore, a correlation term is introduced to constrain the alignment of video frames from different cameras.…”

Section: Optimal Smooth Path For Multiple Camerasmentioning

confidence: 99%

Video stabilization algorithm based on multiple cameras

Jiang,

Xu,

2023

Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023)

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The proposed video stabilization algorithm for head-mounted mobile platforms addresses the issue of video shake. In the feature detection and extraction stage, the Super point feature extraction algorithm is used to extract feature points. This algorithm provides a more comprehensive set of feature points compared to traditional feature detection methods, enabling accurate motion estimation.In the motion smoothing stage, the camera path of a specific camera is preprocessed using Kalman filtering to remove significant shaking factors. Then, the processed path is used as a baseline to simultaneously smooth all camera paths through spatio-temporal optimization, aiming to make the camera paths as similar as possible and reduce distortion. Finally, the optimal path is selected from the refined paths to address the deviation among multiple cameras.Experimental results have demonstrated that this method achieves comparable stability to other methods while significantly reducing the required processing time.

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Section: Optimal Smooth Path For Multiple Camerasmentioning

confidence: 99%