Title
Lost and Found!: associating target persons in camera surveillance footage with smartphone identifiers
Abstract
ABSTRACTWe demonstrate an application of finding target persons on a surveillance video. Each visually detected participant is tagged with a smartphone ID and the target person with the query ID is highlighted. This work is motivated by the fact that establishing associations between subjects observed in camera images and messages transmitted from their wireless devices can enable fast and reliable tagging. This is particularly helpful when target pedestrians need to be found on public surveillance footage, without the reliance on facial recognition. The underlying system uses a multi-modal approach that leverages WiFi Fine Timing Measurements (FTM) and inertial sensor (IMU) data to associate each visually detected individual with a corresponding smartphone identifier. These smartphone measurements are combined strategically with RGB-D information from the camera, to learn affinity matrices using a multi-modal deep learning network.
Year
DOI
Venue
2021
10.1145/3458864.3466904
MOBISYS
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
10
Name
Order
Citations
PageRank
Hansi Liu1232.58
Abrar Alali200.34
Mohamed O. Ibrahim336.82
Hongyu Li414917.22
Marco Gruteser54631309.81
Shubham Jain6146.84
Kristin J. Dana7946115.45
Ashwin Ashok818729.36
Bin Cheng941.49
Hongsheng Lu10718.73