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Automatic detection and tracking of subviral particles in image sequences is an indispensable supportive method for modern medicine research programs. This paper describes the development of a highly adaptable camera-to-world system motion invariant tracking algorithm. A translation compensation is obtained by cross correlations. Particles are detected by an implemented existing algorithm. The detected particles are linked by solving a Linear Assignment Problem. For highly stable results the tracks are improved by Kalman filtering. The algorithm is tested on simulated sequences. The results show a great ability for stable tracking.

Improving subviral particle tracks in fluoroscopic image sequences by global motion compensation