Dynamic Selection of Characteristics for Feature Based Image Sequence Stabilization
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Real-time digital image stabilization system using modified proportional integrated controller
IEEE Transactions on Circuits and Systems for Video Technology
Robust video stabilization to outlier motion using adaptive RANSAC
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Digital image stabilization for humanoid eyes inspired by human VOR system
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
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This paper describes a unified approach for video stabilization. The essential goal is to stabilize image sequences that consist of moving foreground objects, which appear frequently in today's home videos captured by hand-held consumer cameras. Our proposed techniques mainly rely on the analysis of motion content. Three major components are: initialization, segmentation and stabilization. In motion initialization, we propose a novel algorithm to efficiently search for the best possible frame in a sequence to start segmentation. Our segmentation algorithm is based on expectation-maximization (EM) framework which provides the mechanism for simultaneous estimation of motion models and their layers of support. Based on the framework of Kalman filter and EM motion estimation, our proposed algorithm has the flexibility of allowing selective stabilization with respect to background or/and foreground objects, subject to the preferences of customers.