ID-Match: A Hybrid Computer Vision and RFID System for Recognizing Individuals in Groups

Technologies that allow autonomous robots and computer systems to quickly recognize and interact with individuals in a group setting has the potential to enable a wide range of personalized experiences. We present ID-Match, a hybrid computer vision and RFID system that uses a novel reverse synthetic aperture technique to recover the relative motion paths of a RFID tags worn by people and correlate that to physical motion paths of individuals as measured with a 3D depth camera. Results show that our real-time system is capable of simultaneously recognizing and correctly assigning IDs to individuals within 4 seconds with 96.6% accuracy and groups of five people in 7 seconds with 95% accuracy. In order to test the effectiveness of this approach in realistic scenarios, groups of five participants play an interactive quiz game with an autonomous robot, resulting in an ID assignment accuracy of 93.3%.

[1]  Frédéric Lerasle,et al.  Vision and RFID data fusion for tracking people in crowds by a mobile robot , 2010, Comput. Vis. Image Underst..

[2]  Jie Xiong,et al.  ArrayTrack: A Fine-Grained Indoor Location System , 2011, NSDI.

[3]  Lei Yang,et al.  Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices , 2014, MobiCom.

[4]  Gabriel Skantze,et al.  Furhat: A Back-Projected Human-Like Robot Head for Multiparty Human-Machine Interaction , 2011, COST 2102 Training School.

[5]  George W. Quinn,et al.  Report on the Evaluation of 2D Still-Image Face Recognition Algorithms , 2011 .

[6]  Jue Wang,et al.  RF-IDraw: virtual touch screen in the air using RF signals , 2015, SIGCOMM 2015.

[7]  Wolfram Burgard,et al.  Mapping and localization with RFID technology , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[8]  Mahsan Rofouei,et al.  Your phone or mine?: fusing body, touch and device sensing for multi-user device-display interaction , 2012, CHI.

[9]  Charles C. Kemp,et al.  RF vision: RFID receive signal strength indicator (RSSI) images for sensor fusion and mobile manipulation , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  K. V. S. Rao,et al.  Phase based spatial identification of UHF RFID tags , 2010, 2010 IEEE International Conference on RFID (IEEE RFID 2010).

[11]  Martin Vossiek,et al.  UHF RFID Localization Based on Synthetic Apertures , 2013, IEEE Transactions on Automation Science and Engineering.

[12]  Alanson P. Sample,et al.  IDSense: A Human Object Interaction Detection System Based on Passive UHF RFID , 2015, CHI.

[13]  Shuji Hashimoto,et al.  Autonomous Mobile Robot Navigation Using Passive RFID in Indoor Environment , 2009, IEEE Transactions on Industrial Electronics.

[14]  Gaetano Borriello,et al.  SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength , 2000 .

[15]  Wail Gueaieb,et al.  An Intelligent Mobile Robot Navigation Technique Using RFID Technology , 2008, IEEE Transactions on Instrumentation and Measurement.

[16]  W. Brown.  Synthetic Aperture Radar , 1967, IEEE Transactions on Aerospace and Electronic Systems.

[17]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[18]  Ming Yang,et al.  DeepFace: Closing the Gap to Human-Level Performance in Face Verification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[19]  Sherry Hsi,et al.  RFID enhances visitors' museum experience at the Exploratorium , 2005, CACM.

[20]  Samer Al Moubayed,et al.  Regulating Turn-Taking in Multi-child Spoken Interaction , 2015, IVA.

[21]  Axel Pinz,et al.  Fusing RFID and computer vision for probabilistic tag localization , 2014, 2014 IEEE International Conference on RFID (IEEE RFID).

[22]  Joshua Radinsky,et al.  I see you there!: developing identity-preserving embodied interaction for museum exhibits , 2013, CHI.

[23]  K. Jaakkola,et al.  Phase-Based UHF RFID Tracking With Nonlinear Kalman Filtering and Smoothing , 2012, IEEE Sensors Journal.

[24]  Yunhao Liu,et al.  ANDMARC: Indoor Location Sensing Using Active RFID , 2003, PerCom.

[25]  Jue Wang,et al.  Dude, where's my card?: RFID positioning that works with multipath and non-line of sight , 2013, SIGCOMM.

[26]  Xiuwen Liu,et al.  Accurate localization of RFID tags using phase difference , 2010, 2010 IEEE International Conference on RFID (IEEE RFID 2010).