Fast electronic digital image stabilization for off-road navigation
Real-Time Imaging
Fast 3D Stabilization and Mosaic Construction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Image Stabilization by Features Tracking
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Color-Based Video Stabilization for Real-Time On-Board Object Detection on High-Speed Trains
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A novel performance evaluation method of local detectors on non-planar scenes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Full-Frame Video Stabilization with Motion Inpainting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Maximally Stable Extremal Region (MSER) Tracking
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
SIFT Features Tracking for Video Stabilization
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Content-preserving warps for 3D video stabilization
ACM SIGGRAPH 2009 papers
A fully affine invariant image comparison method
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Robust video stabilization based on particle filter tracking of projected camera motion
IEEE Transactions on Circuits and Systems for Video Technology
ACM Transactions on Graphics (TOG)
Improving Video Stabilization in the Presence of Motion Blur
NCVPRIPG '11 Proceedings of the 2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics
Simultaneous inpainting for image structure and texture using anisotropic heat transfer model
Multimedia Tools and Applications
Fast digital image stabilizer based on Gray-coded bit-plane matching
IEEE Transactions on Consumer Electronics
Digital image translational and rotational motion stabilization using optical flow technique
IEEE Transactions on Consumer Electronics
Digital image stabilization with sub-image phase correlation based global motion estimation
IEEE Transactions on Consumer Electronics
An adaptive motion decision system for digital image stabilizer based on edge pattern matching
IEEE Transactions on Consumer Electronics
A Robust Image Alignment Algorithm for Video Stabilization Purposes
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Image Processing
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Video stabilization is an important technique in present day digital cameras as most of the cameras are hand-held, mounted on moving platforms or subjected to atmospheric vibrations. In this paper we propose a novel video stabilization scheme based on estimating the camera motion using maximally stable extremal region features. These features traditionally used in wide baseline stereo problems were never explored for video stabilization purposes. Through our extensive experiments show we how some properties of these region features are suitable for the stabilization task. After estimating the global camera motion parameters using these region features, we smooth the motion parameters using a gaussian filter to retain the desired motion. Finally, motion compensation is carried out to obtain a stabilized video sequence. A number of examples on real and synthetic videos demonstrate the effectiveness of our proposed approach. We compare our results to existing techniques and show how our proposed approach compares favorably to them. Interframe Transformation Fidelity is used for objective evaluation of our proposed approach.