Human Activity Recognition using Simple Direct Sensors – Henry Kautz (University of Rochester)

June 23, 2010 all-day

Simple, inexpensive sensors, including RFID-based object touch sensors, GPS location sensors, and cell-phone quality accelerometers, can be used to detect and distinguish a wide range of human activities with surprisingly high accuracy. I will provide an overview of hardware and algorithms for direct sensing, and speculate about how such sensor data could be used for embodied language and task learning.

Johns Hopkins University

Johns Hopkins University, Whiting School of Engineering

Center for Language and Speech Processing
Hackerman 226
3400 North Charles Street, Baltimore, MD 21218-2680

Center for Language and Speech Processing