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KinSpace: Passive obstacle detection via Kinect

Title
KinSpace: Passive obstacle detection via Kinect
Authors
Greenwood, C.Nirjon, S.Stankovic, J.Yoon, Hee JungRa, Ho-KyeongSon, SangPark, Taejoon
DGIST Authors
Yoon, Hee Jung; Ra, Ho-Kyeong; Son, Sang; Park, Taejoon
Issue Date
2014
Citation
11th European Conference on Wireless Sensor Networks, EWSN 2014, 8354 LNCS, 182-197
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
ISSN
0302-9743
Abstract
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 space of an environment through observation of resident walking patterns. It then monitors the open space 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 a 5,000-frame deployment dataset spanning multiple homes and classes of objects. 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 deployment in an actual home show roughly 80% accuracy for both open space detection and 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. © 2014 Springer International Publishing.
URI
http://hdl.handle.net/20.500.11750/3774
DOI
10.1007/978-3-319-04651-8_12
Publisher
Springer
Related Researcher
  • Author Son, Sang Hyuk RTCPS(Real-Time Cyber-Physical Systems Research) Lab
  • Research Interests
Files:
There are no files associated with this item.
Collection:
Information and Communication EngineeringETC2. Conference Papers
ETC2. Conference Papers
School of Undergraduate Studies2. Conference Papers


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