Details
| Original language | English |
|---|---|
| Title of host publication | 4th Pacific-Rim Symposium on Image and Video Technology |
| Subtitle of host publication | Proceedings, PSIVT 2010 |
| Pages | 52-57 |
| Number of pages | 6 |
| Publication status | Published - Dec 2010 |
| Event | 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010 - Singapore, Singapore Duration: 14 Nov 2010 → 17 Nov 2010 |
Publication series
| Name | Proceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010 |
|---|
Abstract
We propose a novel context based human fall detection mechanism in real home environment. Fall incidents are detected using head and floor information. The centroid location of the head and feet from each frame are used to learn a context model consisting of normal head and floor blocks. Every floor block has its associated Gaussian distribution, representing a set of head blocks. This Gaussian distribution defines standard vertical distance as average height of an object at that specific floor block. The classification of blocks and average height is later used to detect a fall. Fall detection methods often detect bending situations as fall. This method is able to distinguish bending and sitting from falling. Furthermore, a fall into any direction and at any distance from camera can be detected. Evaluation results show the robustness and high accuracy of the proposed approach.
Keywords
- Context model, Elderly, Fall detection, Surveillance, View-invariant
ASJC Scopus subject areas
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Software
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4th Pacific-Rim Symposium on Image and Video Technology: Proceedings, PSIVT 2010. 2010. p. 52-57 5673986 (Proceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - View-invariant Fall Detection for Elderly in Real Home Environment
AU - Shoaib, Muhammad
AU - Dragon, Ralf
AU - Ostermann, Jörn
PY - 2010/12
Y1 - 2010/12
N2 - We propose a novel context based human fall detection mechanism in real home environment. Fall incidents are detected using head and floor information. The centroid location of the head and feet from each frame are used to learn a context model consisting of normal head and floor blocks. Every floor block has its associated Gaussian distribution, representing a set of head blocks. This Gaussian distribution defines standard vertical distance as average height of an object at that specific floor block. The classification of blocks and average height is later used to detect a fall. Fall detection methods often detect bending situations as fall. This method is able to distinguish bending and sitting from falling. Furthermore, a fall into any direction and at any distance from camera can be detected. Evaluation results show the robustness and high accuracy of the proposed approach.
AB - We propose a novel context based human fall detection mechanism in real home environment. Fall incidents are detected using head and floor information. The centroid location of the head and feet from each frame are used to learn a context model consisting of normal head and floor blocks. Every floor block has its associated Gaussian distribution, representing a set of head blocks. This Gaussian distribution defines standard vertical distance as average height of an object at that specific floor block. The classification of blocks and average height is later used to detect a fall. Fall detection methods often detect bending situations as fall. This method is able to distinguish bending and sitting from falling. Furthermore, a fall into any direction and at any distance from camera can be detected. Evaluation results show the robustness and high accuracy of the proposed approach.
KW - Context model
KW - Elderly
KW - Fall detection
KW - Surveillance
KW - View-invariant
UR - http://www.scopus.com/inward/record.url?scp=78751678914&partnerID=8YFLogxK
U2 - 10.1109/PSIVT.2010.16
DO - 10.1109/PSIVT.2010.16
M3 - Conference contribution
AN - SCOPUS:78751678914
SN - 9780769542850
T3 - Proceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010
SP - 52
EP - 57
BT - 4th Pacific-Rim Symposium on Image and Video Technology
T2 - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010
Y2 - 14 November 2010 through 17 November 2010
ER -