Efficient object-based video inpainting

Authors:
M. Vijay Venkatesh;Sen-ching Samson Cheung;Jian Zhao
Affiliations:
Center for Visualization and Virtual Environments, Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40507, USA;Center for Visualization and Virtual Environments, Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40507, USA;Center for Visualization and Virtual Environments, Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40507, USA
Venue:
Pattern Recognition Letters
Year:
2009

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Abstract

Video inpainting is the process of repairing missing regions (holes) in videos. Most automatic techniques are computationally intensive and unable to repair large holes. To tackle these challenges, a computationally-efficient algorithm that separately inpaints foreground objects and background is proposed. Using Dynamic Programming, foreground objects are holistically inpainted with object templates that minimizes a sliding-window dissimilarity cost function. Static background are inpainted by adaptive background replacement and image inpainting.