Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
SIFT Features Tracking for Video Stabilization
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Feature-Based Full-Frame Image Stabilization
ISM '07 Proceedings of the Ninth IEEE International Symposium on Multimedia
Robust video stabilization based on particle filter tracking of projected camera motion
IEEE Transactions on Circuits and Systems for Video Technology
A Central Sub-image Based Global Motion Estimation Method for In-Car Video Stabilization
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
International Journal of Wireless and Mobile Computing
EDA-USL: unsupervised clustering algorithm based on estimation of distribution algorithm
International Journal of Wireless and Mobile Computing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
A wireless vehicle surveillance system mixed QoS controls
International Journal of Wireless and Mobile Computing
Fast digital image stabilizer based on Gray-coded bit-plane matching
IEEE Transactions on Consumer Electronics
Digital image stabilization by adaptive block motion vectors filtering
IEEE Transactions on Consumer Electronics
Digital image stabilization based on statistical selection of feasible regions
IEEE Transactions on Consumer Electronics
System-on-Chip Solution of Video Stabilization for CMOS Image Sensors in Hand-Held Devices
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Image Processing
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A novel digital video stabilisation approach that uses salient features and particle filter for global motion estimation is proposed in this paper. In this approach, the local salient features are first gained by the improved K-means clustering method using the features obtained from the Scale Invariant Feature Transform SIFT feature points extracted from the down-sampled images, and then the salient regions are located in the video frames. The trajectory of the features extracted from the salient regions is used to estimate global motion between frames. A new similarity function called SRMSE Salient Region Mean Square Error is proposed in particle filter framework to reduce the computational cost. Motion compensation yields stabilised video sequences using the estimates. Experimental results demonstrate that the proposed algorithm has good performance and improves the efficiency significantly.