Comparison of Tracking Methods in Respect of Automation of an Animal Behavioral Test

Abstract

Automation in experiments carried out on animals is getting more and more important in research. Computers take over laborious and time-consuming activities like recording and analysing images of the experiment scene. The first step in an image analysis is finding and distinguishing between the observed animals and then tracking all objects during the experiment. In this paper four tracking methods are presented. Quantitative and qualitative figures of merit are applied to confront those methods. The comparison takes into consideration the level of correct object recognition during different disturbances, the speed of computation, requirements as to the frame rate and image illumination, quality of recovering from occluded situations and others.

Stars’ Centroid Determination Using PSF-Fitting Method

“…The centroid detection has to be preceded by filtering out the image distortions. Many different computation methods are adopted to reduce the image distortions [7][8][9][10]. Mathematically simplest methods are based on computing the centre of mass [11] and the weighted centre of mass [12][13][14] of a star, respectively.…”