This paper describes a novel set of algorithms that allows indoor activity to be monitored using data from very low
resolution imagers and other non-intrusive sensors. The objects are not resolved but activity may still be determined.
This allows the use of such technology in sensitive environments where privacy must be maintained. Spectral un-mixing
algorithms from remote sensing were adapted for this environment. These algorithms allow the fractional contributions
from different colours within each pixel to be estimated and this is used to assist in the detection and monitoring of small
objects or sub-pixel motion.
In recent years, closed circuit cameras have become a common feature of urban life. There are environments however
where the movement of people needs to be monitored but high resolution imaging is not necessarily desirable: rooms
where privacy is required and the occupants are not comfortable with the perceived intrusion. Examples might include
domiciliary care environments, prisons and other secure facilities, and even large open plan offices. This paper
discusses algorithms that allow activity within this type of sensitive environment to be monitored using data from low
resolution cameras (ones where all objects of interest are sub-pixel and cannot be resolved) and other non-intrusive
sensors. The algorithms are based on techniques originally developed for wide area reconnaissance and surveillance
applications. Of particular importance is determining the minimum spatial resolution that is required to provide a
specific level of coverage and reliability.
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