Abstract
This article details the development and testing of an empirical data capture system with the ability to collect spatial-frequency statistics relating to the movement behaviour of a smart home inhabitant. This is achieved using a greyscale normalised cross-correlation pattern matching algorithm. Environmental obstructions on the floor space can also be inferred from a visual representation of the accumulated data. Whilst this methodology itself is not novel, its application to person tracking specifically within a smart home environment does not appear in the literature and is considered a novel approach. The results of tests performed on the pattern matching technique show a tracking competency rate of 94.45% with a standard deviation of 0.009027, indicating high fidelity across a wide variety of environmental factors.
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Poland, M.P., Nugent, C.D., Wang, H. et al. Spatial-frequency data acquisition using rotational invariant pattern matching in smart environments. Ann. Telecommun. 65, 557–570 (2010). https://doi.org/10.1007/s12243-010-0172-4
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DOI: https://doi.org/10.1007/s12243-010-0172-4