Computer Science Colloquia
Friday, October 9, 2015
Advisor: Kamin Whitehouse
Attending Faculty: Jack Stankovic (Chair); James Scott (Microsoft Research, Cambridge, UK), Gabriel Robins and Laura Barnes
9:00 AM, Rice Hall, Rm. 404
PhD Proposal Presentation
Object User Recognition Using Smart Wearable Devices
Context-aware computing is now an integral part of many commercial 'smart' products. Some examples of the contexts used are home occupancy, road traffic, and global position coordinates. Identity of a person is also an important context for many ubiquitous computing applications. For example, some bathroom scales can recognize the person stepping on them to provide long-term weight and other body measurement trends. In order for objects to perform personalized or contextual functions based on the object user's identity, they must solve what we call the object user recognition problem: understanding who is actually using an object.
Many techniques have already been designed to solve this problem. Some objects, such as computers or smartphones, identify a user based on a pass code or fingerprint. Other techniques use RFID tags to detect when a person's hand is near an object, or thermal cameras to detect when a person wearing a unique thermal tag is near an object. Other objects that have embedded sensors can recognize the object user based on the unique way in which an object is touched or held. In our research, we hypothesize that it is possible to perform object user recognition using sensors currently available in commercial smart wrist devices. These sensors provide rich information about the location and hand gestures of the device bearer. We speculate that this information is sufficient to identify an object user from the set of possible people, with access to the object.