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  1. University of Computer Studies, Yangon
  2. Conferences

Geometric Kinect Joints Computing for Human Fall Recognition

http://hdl.handle.net/20.500.12678/0000003422
http://hdl.handle.net/20.500.12678/0000003422
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d6842e9a-b542-4feb-8774-69ef5ca2424b
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ICCA ICCA 2019 Proceedings Book-pages-100-105.pdf (604 Kb)
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Article
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Publication
Title
Title Geometric Kinect Joints Computing for Human Fall Recognition
Language en
Publication date 2019-02-27
Authors
Htoo, Chit Kyin
Sein, Myint Myint
Description
This paper proposes an computing analysis onhuman geometric shape features to detect a fallbehavior. The system mainly computes the changeson human orientation (torso angle) and centroidheight via the human skeleton joints extracted byKinect sensor. The system computes and tracks thespatial changes of these human orientation andcentroid height and distinguishs a fall behavioramong other daily activities by using a thresholdingalgorithm. The main objective of this computation isto minize the computational time and to increase thetrue alarms in developing a fall detection. The systemworks the feature extraction on our collected falldetection dataset containing the fall data along withdaily activities such as sitting down, lying, combing.Standing, etc., are collected by Microsoft Kinectsensor.
Keywords
Fall Detection, Image Processing, Skeleton Joint Extraction, Geometric Computing, Microsoft Kinect Sensor
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1175
Journal articles
Seventeenth International Conference on Computer Applications(ICCA 2019)
Conference papers
Books/reports/chapters
Thesis/dissertations
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