Authors:
Harish Bhaskar
and
Helmut Bez
Affiliation:
Research School of Informatics, Loughborough University, United Kingdom
Keyword(s):
Video stabilization, motion compensation, motion estimation, genetic algorithms, kalman filtering.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Image Processing
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Robotics and Automation
;
Soft Computing
;
Vision, Recognition and Reconstruction
Abstract:
Video stabilization algorithms primarily aim at generating stabilized image sequences by removing unwanted shake due to small camera movements. It is important to perform video stabilization in order to assure more effective high level video analysis. In this paper, we propose novel motion correction schemes based on probabilistic filters in the context of block matching motion estimation for efficient video stabilization. We present a detailed overview of the model and compare our model against other block matching schemes on several real-time and synthetic data sets.