The Carpet Knows: Identifying People in a Smart Environment from a Single Step

Bo Zhou, Monit Shah Singh, Sugandha Doda, Muhammet Yildirim, Jingyuan Cheng, Paul Lukowicz

In: First International Workshop on Pervasive Smart Living Spaces PerCom Workshops 2017. IEEE International Conference on Pervasive Computing and Communications (PerCom-17) March 13-17 Kona Hawaii United States IEEE 2017.


In this paper, we present an approach for person identification using morphing footsteps measured from a fabric-based pressure mapping sensor system. The flexible fabric sensor is 0.5 mm thin and operates under a 5 mm thick normal carpet; therefore, it can be easily implemented into modern smart living spaces. We extract features concerning single steps with the shifting of gravity center, maximum pressure point and overall pressed area, which are independent from shape details and inter-step relationships of the walking sequences. The system is evaluated with 13 participants wearing shoes and walking normally across the carpet. Overall 529 footsteps are recorded, and the resulting average identification accuracy is 76.9%. Our approach can also be used for further activity recognition with the same physical carpet sensors.

1570326143_(1).pdf (pdf, 3 MB )

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz