TY - GEN
T1 - Beyond Video Surveillance
T2 - 2022 IEEE Wireless Communications and Networking Conference (WCNC 2022)
AU - Fan, Zhuochen
AU - Liu, Tian
AU - Huang, Jun
AU - Yang, Tong
PY - 2022
Y1 - 2022
N2 - Video cameras have been widely deployed at city-scale for security surveillance. However, under poor light condition and limited video resolution, it is often impossible to determine the identity of a pedestrian by using computer vision alone. Motivated by the fast and continuous penetration of smartphones, in this paper, we explore the feasibility of augmenting video cameras to 'see' the identities of smartphones (e.g., MAC addresses, cellular IDs, or even phone numbers) carried by pedestrians. We develop IDCam-a system that integrates a video camera with a smart antenna array, which leverages spatial-domain sensing of smartphone's sleep-talk (i.e., the packets transmitted by apps while the phone's screen is off) to match the angles of smartphone's packets and pedestrians in the video, enabling passive identity linking without the cooperation of target. Experiment results show that IDCam accurately links visual and wireless identities in a complex deployment environment with tens of pedestrians and intensive multipath signal propagation.
AB - Video cameras have been widely deployed at city-scale for security surveillance. However, under poor light condition and limited video resolution, it is often impossible to determine the identity of a pedestrian by using computer vision alone. Motivated by the fast and continuous penetration of smartphones, in this paper, we explore the feasibility of augmenting video cameras to 'see' the identities of smartphones (e.g., MAC addresses, cellular IDs, or even phone numbers) carried by pedestrians. We develop IDCam-a system that integrates a video camera with a smart antenna array, which leverages spatial-domain sensing of smartphone's sleep-talk (i.e., the packets transmitted by apps while the phone's screen is off) to match the angles of smartphone's packets and pedestrians in the video, enabling passive identity linking without the cooperation of target. Experiment results show that IDCam accurately links visual and wireless identities in a complex deployment environment with tens of pedestrians and intensive multipath signal propagation.
KW - array signal processing
KW - computer vision
KW - object detection
KW - sensor fusion
UR - http://www.scopus.com/inward/record.url?scp=85130683725&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85130683725&origin=recordpage
U2 - 10.1109/WCNC51071.2022.9771759
DO - 10.1109/WCNC51071.2022.9771759
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-1-6654-4267-1
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 1922
EP - 1927
BT - 2022 IEEE Wireless Communications and Networking Conference (WCNC)
PB - IEEE
Y2 - 10 April 2022 through 13 April 2022
ER -