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Day or Night Activity Recognition From Video Using Fuzzy Clustering Techniques
- Source :
- IEEE Transactions on Fuzzy Systems. 22:483-493
- Publication Year :
- 2014
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2014.
-
Abstract
- We present an approach for activity state recognition implemented on data collected from various sensors—standard web cameras under normal illumination, web cameras using infrared lighting, and the inexpensive Microsoft Kinect camera system. Sensors such as the Kinect ensure that activity segmentation is possible during the daytime as well as night. This is especially useful for activity monitoring of older adults since falls are more prevalent at night than during the day. This paper is an application of fuzzy set techniques to a new domain. The approach described herein is capable of accurately detecting several different activity states related to fall detection and fall risk assessment including sitting, being upright, and being on the floor to ensure that elderly residents get the help they need quickly in case of emergencies and ultimately to help prevent such emergencies.
- Subjects :
- Image moment
Fuzzy clustering
Computer science
business.industry
Applied Mathematics
Fuzzy set
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Sitting
Activity recognition
Activity monitoring
Computational Theory and Mathematics
Artificial Intelligence
Control and Systems Engineering
Segmentation
Computer vision
Artificial intelligence
business
Fall risk assessment
Subjects
Details
- ISSN :
- 19410034 and 10636706
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Fuzzy Systems
- Accession number :
- edsair.doi...........e0ebff03c9e919dc73e75449d2251aca