Qualitative Modelling and Analysis of Animal Behaviour
Applied Intelligence
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Abstract: We present a working system for real-time tracking of multiple laboratory animals. As it is usually possible to ensure good contrast between the animals and the background, the tracking of a single animal or several physically separated animals can be obtained by relatively simple algorithms. The main problem arises when we try to track several almost identical, uniformly coloured animals during their contacts. To deal with this problem we utilize dynamic information extracted by estimating sparse optical flow along the object contours. Optical flow vectors are used for updating the positions of the tracked contours in a sequence of image frames. The local properties of optical flow enable the system to track the objects during their contact, although some parts of object contours become hidden. The missing dynamic information is reconstructed by using a model of constant optical flow along an object contour. The reconstructed contours are then adjusted to real object boundaries in the current frame by using an active contour model. The robustness of the tracking algorithmis improved by adding a supervision module, which detects tracking failures and reinitialises the contours that lose their targets. The system has been tested on real sequences with laboratory animals during pharmacological experiments and has been shown to be robust and efficient. Future extensions will include expert knowledge of biomedical and pharmacological experts. The major goal is to build a system that will provide objective and standardised tool for evaluation of animal behaviour during experiments.