19 May 2009 Correlating spatial-temporal event likelihood to security objectives and detection
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Abstract
To evaluate security systems, the observer must be analyzed relative to the area of observation and targets expected to be observed therein. The algorithm constructs a probability model for detection in both spatial and temporal references within the area of observation. Targets must be identified with characteristics such as size and event-duration. Additional criteria from a physical security risk assessment can characterize the area of observation and expected targets. Inputs for the equations include base terrain coordinates in a regularly-gridded system, expected viewobstruction changes across a time period, sensor and recording limitations, and events of interest. An event is an action of a physical nature in which the observation platform is expected to detect, corroborate, or validate the occurrence. Temporal and spatial models of observation system weaknesses are generated, and optimal sensor positioning is computed under constraints. Incorporating this into the results allows for consideration that a sensor system may only provide limited characteristics of an event to help identify objects or individuals within the scene. Consideration is given to the ability to immediately respond to an event or place reliance on the system for evidentiary purposes. The rigorous algorithm can be used to analyze physical site security; to identify improvements in observation platforms; and to compute optimal sensor placement. Noted constraints of the current research include optical sensors, predictable obstruction causes, and sensor-placement with characterized pan-tilt-zoom functionality.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthew T. Altman, Matthew T. Altman, } "Correlating spatial-temporal event likelihood to security objectives and detection", Proc. SPIE 7352, Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, 73520O (19 May 2009); doi: 10.1117/12.818438; https://doi.org/10.1117/12.818438
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