A framework for spatiotemporal control in the tracking of visual contours
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Video Processing and Communications
Video Processing and Communications
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A block-based gradient descent search algorithm for block motion estimation in video coding
IEEE Transactions on Circuits and Systems for Video Technology
Hi-index | 0.00 |
In object tracking, complex background frequently forms local maxima that tend to distract tracking algorithms from the real target. In order to reduce such risks, we utilize an adaptive Kalman filter to predict the initial searching point in the space of coordinate transform parameters so that both tracking reliability and computational simplicity is significantly improved. Our method tracks the changing rate of the transform parameters and makes prediction on future values of the transform parameters to determine the initial searching point. More importantly, noises in the Kalman filter are effectively estimated in our approach without any artificial assumption, which makes our method able to adapt to various target motions and searching step sizes without any manual intervention. Simulation results demonstrate the effectiveness of our algorithm.