Image sequence stabilization in real time
Real-Time Imaging
Fast electronic digital image stabilization for off-road navigation
Real-Time Imaging
Recognition, Resolution, and Complexity of Objects Subject to Affine Transformations
International Journal of Computer Vision
A RKHS Interpolator-Based Graph Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Full-Frame Video Stabilization with Motion Inpainting
IEEE Transactions on Pattern Analysis and Machine Intelligence
A stable vision system for moving vehicles
IEEE Transactions on Intelligent Transportation Systems
Digital image translational and rotational motion stabilization using optical flow technique
IEEE Transactions on Consumer Electronics
Digital image stabilization based on circular block matching
IEEE Transactions on Consumer Electronics
Video stabilization based on saliency driven SIFT matching and discriminative RANSAC
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
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In this paper, a video stabilization technique is presented. There are four steps in the proposed approach. We begin with extracting feature points from the input image using the Lowe SIFT (Scale Invariant Feature Transform) point detection technique. This set of feature points is then matched against the set of feature points detected in the previous image using the Wyk et al. RKHS (Reproducing Kernel Hilbert Space) graph matching technique. We can calculate the camera motion between the two images with the aid of a 3D motion model. Expected and unexpected components are separated using a motion taxonomy method. Finally, a full-frame technique to fill up blank image areas is applied to the transformed image.