Towards robust device-free passive localization through automatic camera-assisted recalibration

Authors:
Chenren Xu;Mingchen Gao;Bernhard Firner;Yanyong Zhang;Richard Howard;Jun Li
Affiliations:
Rutgers University, North Brunswick, NJ;Rutgers University, Piscataway, NJ;Rutgers University, North Brunswick, NJ;Rutgers University, North Brunswick, NJ;Rutgers University, North Brunswick, NJ;Rutgers University, North Brunswick, NJ
Venue:
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Year:
2012

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Abstract

Device-free passive localization (DfP) techniques can localize human subjects without wearing a radio tag. Being convenient and private, DfP can find many applications in ubiquitous/pervasive computing. Unfortunately, DfP techniques need frequent manual recalibration of the radio signal values, which can be cumbersome and costly. We present SenCam, a sensor-camera collaboration solution that conducts automatic recalibration by leveraging existing surveillance camera(s). When the camera detects a subject, it can periodically trigger recalibration and update the radio signal data accordingly. This technique requires camera access occasionally each month, minimizing computational costs and reducing privacy concerns when compared to localization techniques solely based on cameras. Through experiments in an open indoor space, we show that this scheme can retain good localization results while avoiding manual recalibration.