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Computer Science Colloquia

Tuesday, July 16, 2013
Chris Greenwood
Advisor: John A. Stankovic
Attending Faculty: Alf Weaver

1:00 PM, Rice Hall, Rm. 242

Master's Project Presentation
KinSpace: Obstacle Detection via Kinect


Falls are a significant problem for the elderly living independently in the home. Many falls occur due to household objects left in open spaces. We present KinSpace, a passive obstacle detection system for the home. KinSpace employs the use of a Kinect sensor to learn the open spaces of an environment through observation of resident walking patterns. It then monitors those open spaces for obstacles that are potential tripping hazards and notifies the residents accordingly. KinSpace uses real-time depth data and human-in-the-loop feedback to adjust its understanding of the open space of an environment. We present results showing the effectiveness of our underlying technical solutions in identifying open spaces and obstacles. The results for both lab testing and a small deployment in an actual home show over 80% accuracy for open space detection and 70% accuracy in obstacle detection even in the presence of many real world issues. Consequently, this new technology shows great potential to reduce the risk of falls in the home due to environmental hazards.