Computation of component image velocity from local phase information
International Journal of Computer Vision
Phase-based disparity measurement
CVGIP: Image Understanding
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
Fast electronic digital image stabilization for off-road navigation
Real-Time Imaging
Performance characterization of image stabilization algorithms
Real-Time Imaging
Understanding the Behavior of SFM Algorithms: A Geometric Approach
International Journal of Computer Vision
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Shooting a smooth video with a shaky camera
Machine Vision and Applications
On-Road Vehicle Detection: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Full-Frame Video Stabilization with Motion Inpainting
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A phase-based approach to the estimation of the optical flow field using spatial filtering
IEEE Transactions on Neural Networks
A compact harmonic code for early vision based on anisotropic frequency channels
Computer Vision and Image Understanding
Multimedia Tools and Applications
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We introduce a novel video stabilization method that enables the extraction of optic flow from short unstable sequences. Contrary to traditional stabilization techniques that use approximative global motion models to estimate the full camera motion, our method estimates the unstable component of the camera motion only. This allows for the use of simpler global motion models, and at the same time extends the validity to more complex environments, such as close scenes that contain independently moving objects. The unstable component of the camera motion is derived from a maximization of the temporal local velocity constancy over the entire short sequence. The method, embedded within a phase-based optic flow algorithm, is tested on both synthetic and complex real-world sequences. The optic flow obtained using our technique is denser than that extracted directly from the original sequence, and from a sequence stabilized with a more traditional stabilization technique.