Abstract
A temporal modelling and prediction scheme based on modelling a ‘history space’ using Gaussian mixture models is presented. A point in this space represents an abstraction of a complete object history as opposed to finite histories used in Markov methods. It is shown how this ‘History Space Classifier’ may be incorporated into an existing scheme for spatial object modelling and tracking to improve tracking speed and robustness and to classify object ‘behaviour’ into normal and abnormal. An application to the tracking and monitoring of livestock is also presented in this paper.
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Magee, D.R., Boyle, R.D. (2000). Spatio-Temporal Modeling in the Farmyard Domain. In: Nagel, HH., Perales López, F.J. (eds) Articulated Motion and Deformable Objects. AMDO 2000. Lecture Notes in Computer Science, vol 1899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722604_8
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DOI: https://doi.org/10.1007/10722604_8
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