Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Covariance Tracking using Model Update Based on Lie Algebra
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Real-Time Tracking of the Shoot Point from Light Pen Based on Camshift
ICINIS '08 Proceedings of the 2008 First International Conference on Intelligent Networks and Intelligent Systems
Robust Face Track Finding in Video Using Tracked Points
SITIS '08 Proceedings of the 2008 IEEE International Conference on Signal Image Technology and Internet Based Systems
Visual Tracking via Particle Filtering on the Affine Group
International Journal of Robotics Research
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This paper proposes an accurate method for multiple key points tracking in long microscopic sequences. Tracking in normal-scale image sequences is proved to be a valuable fundamental technology in computer vision, while tracking in microscopic sequences is a more challenging work due to its poor image quality resulted from the complexity of microscopic imaging process. The micro stereo imaging process can be implemented in a tilting rotation of the stage which produces an affine geometric transformation on the projection of rigid spatial micro structure. This paper finds that the projection's affine invariance leads tracking of point templates to be a feasible solution, due to the fixed spatial relationship among the composed of simple fundamental components such as points, lines and planes. At the same time, we apply an adaptive particle filter (PF) of points tracking algorithm to sample and calculate the weights from those multiple point templates, which can resolve the visual distortion, illumination variability and irregular motion estimation. The experimental results are precise and robust for rigid multiple key points tracking in long micro image sequences.