Fusion of security camera and RSS fingerprinting for indoor multi-person tracking

In this paper the fusion of data from a network of security cameras and RSS fingerprint observations are combined to facilitate the simultaneous tracking of multiple persons inside indoor environments. An objective of the developed algorithm is to utilize existing building infrastructure namely the networks of security cameras and WiFi access points. Additionally minimal initial and maintenance calibration is required as crowdsourcing of the fingerprint mapping and self-calibrating camera processing is an integral component of the algorithm. Experimental results are given that demonstrate the accuracy, robustness and adaptability of the developed tracking algorithm.