Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
CeDAR: A real-world vision system: Mechanism, control and visual processing
Machine Vision and Applications
Full-Frame Video Stabilization with Motion Inpainting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Stabilization Using Scale-Invariant Features
IV '07 Proceedings of the 11th International Conference Information Visualization
An Introduction to Inertial and Visual Sensing
International Journal of Robotics Research
SIFT Features Tracking for Video Stabilization
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Cerebellar-inspired adaptive control of a robot eye actuated by pneumatic artificial muscles
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Digital image stabilizing algorithms based on bit-plane matching
IEEE Transactions on Consumer Electronics
Selective object stabilization for home video consumers
IEEE Transactions on Consumer Electronics
Digital video stabilization through curve warping techniques
IEEE Transactions on Consumer Electronics
Robust digital image stabilization using the Kalman filter
IEEE Transactions on Consumer Electronics
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In this paper, a new Digital Image Stabilization (DIS) system is for humanoid eyes presented. This DIS system was biologically inspired by the human Vestibulo-Ocular Reflex (VOR) system, and is based on a KLT tracker and an Inertial Measurement Unit (IMU). In order to more accurately estimate the motion between two consecutive image frames, corresponding points that were discovered by KLT tracker and IMU were used. The initial motion that was estimated with the IMU was incorporated into the KLT tracker in order to improve the speed and accuracy of the tracking process. Also, a Kalman filter was applied to remove unwanted camera motion. The experimental results showed that the proposed DIS system has the characteristics of the high speed and accuracy in various conditions.