DocumentCode
3071280
Title
Kinect in neurorehabilitation: Computer vision system for real time hand and object detection and distance estimation
Author
Strbac, M. ; Markovic, Marko ; Popovic, Dejan B.
Author_Institution
Signals & Syst. Dept., Univ. of Belgrade, Belgrade, Serbia
fYear
2012
fDate
20-22 Sept. 2012
Firstpage
127
Lastpage
132
Abstract
This paper presents image processing and scene analysis methods that can provide artificial vision that is of interest for automatic selection of hand trajectory and prehension. The new algorithm, which uses data from the Kinect sensor, allows real-time detection of the hand of the person grasping an object at working table in front of that person. The outputs are real world coordinates of the hand and the object. The image processing is done in Matlab over the depth image stream taken from the Microsoft Kinect as a sensory input. Results show that in the presented system setup our program is capable of tracking hand movements in the transverse plane and estimating hand and object position in real-time with tolerable estimation error for the selection of stimulation paradigm that could control hand trajectory.
Keywords
computer vision; image motion analysis; medical image processing; neuromuscular stimulation; object detection; object tracking; patient rehabilitation; position measurement; FET; Kinect sensor; Matlab; Microsoft Kinect; artificial vision; computer vision system; depth image stream; distance estimation; estimation error; functional electrical therapy; hand coordinates; hand movement tracking; hand position estimation; hand prehension; hand trajectory control; image processing; neurorehabilitation; object coordinates; object detection; object grasping; object position estimation; real time hand detection; scene analysis method; sensory input; stimulation paradigm; transverse plane; working table; Estimation; Image edge detection; Mathematical model; Real-time systems; Robot sensing systems; Streaming media; Microsoft Kinect; RANSAC optimization; functional electrical therapy; hand tracking; object detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
Conference_Location
Belgrade
Print_ISBN
978-1-4673-1569-2
Type
conf
DOI
10.1109/NEUREL.2012.6419983
Filename
6419983
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