Full-frame video stabilization with motion inpainting

Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. We propose a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality. While most previous methods end up with pr...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2006-07, Vol.28 (7), p.1150-1163
Main Authors: Matsushita, Y., Ofek, E., Weina Ge, Xiaoou Tang, Heung-Yeung Shum
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial intelligence
Cameras
Computer Graphics
Computer science
control theory
systems
Consistency
Exact sciences and technology
Filling
Frames
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image motion analysis
Image quality
Information Storage and Retrieval - methods
Layout
Motion
Motion analysis
Motion estimation
motion inpainting
Numerical Analysis, Computer-Assisted
Pattern analysis
Pattern recognition. Digital image processing. Computational geometry
Photography - methods
Pixel
Point spread functions
Reproducibility of Results
Robustness
Sensitivity and Specificity
sharpning and deblurring
Signal Processing, Computer-Assisted
Stabilization
Subtraction Technique
Video analysis
video completion
video enhancement
Video Recording - methods
Video sequences
video stabilization
Visual
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Description
Summary:Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. We propose a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality. While most previous methods end up with producing smaller size stabilized videos, our completion method can produce full-frame videos by naturally filling in missing image parts by locally aligning image data of neighboring frames. To achieve this, motion inpainting is proposed to enforce spatial and temporal consistency of the completion in both static and dynamic image areas. In addition, image quality in the stabilized video is enhanced with a new practical deblurring algorithm. Instead of estimating point spread functions, our method transfers and interpolates sharper image pixels of neighboring frames to increase the sharpness of the frame. The proposed video completion and deblurring methods enabled us to develop a complete video stabilizer which can naturally keep the original image quality in the stabilized videos. The effectiveness of our method is confirmed by extensive experiments over a wide variety of videos
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/TPAMI.2006.141