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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/188
Title: An automatic natural feature selection system for indoor tracking - application to Alzheimer patient support
Authors: Badeche, Mohamed 
Bousefsaf, Frédéric 
Moussaoui , Abdelhak 
Benmohammed, Mohamed 
Pruski, Alain 
Affiliations: Faculty of Information and Communication Technology (ICT) 
Faculty of Information and Communication Technology (ICT) 
Keywords: Natural Features;Matching;Local Descriptor;Optical Flow;Alzheimer Disease;Augmented Reality Glasses
Issue Date: 2018
Journal: International Journal of Computational Vision and Robotics 
Volume: 8
Issue: 2
Abstract: 
In this paper, we propose an automatic selection and natural feature tracking method that uses a monocular camera for path capturing and guides the user showing him the path to be followed. The application targets Alzheimer patients for helping them in their indoor moves. By offering an automatic selection of features, the user intervention and prior knowledge of the working environment would not be required to assure the good working of the system. The general principle of the proposed method is to record the path to be followed, and then recognise it in real time using purely visual methods, using only a single camera as an acquisition sensor. The devised system could be implemented on augmented-reality glasses with one single built-in camera. The experimental results have shown that the proposed method is very promising and the application could follow accurately the required path in real time, with a satisfying robustness in a fully-contrasted and static environment.
URI: http://dspace.univ-constantine2.dz/handle/123456789/188
ISSN: 1752-9131, 1752-914X
DOI: 10.1504/IJCVR.2018.091982
Appears in Collections:Journal Articles

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