Authors:
Julia Richter
;
Christian Wiede
and
Gangolf Hirtz
Affiliation:
Chemnitz University of Technology, Germany
Keyword(s):
Pose Estimation, Stereo Vision, Image Understanding, Video Analysis, 3-D Image Processing, Machine Learning, Support Vector Machine, Ambient Assisted Living.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Cardiovascular Imaging and Cardiography
;
Cardiovascular Technologies
;
Computer Vision, Visualization and Computer Graphics
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Image Understanding
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Signal Processing
;
Software Engineering
;
Video Analysis
Abstract:
The European population will steadily be growing older in the following decades. At the same time, the risk of
getting dementia increases with higher age. Both these factors are apt to cause serious problems for the society,
especially with regard to the caring sector, which also suffers from the lack of qualified personnel. As technical
support systems can be of assistance to medical staff and patients, a mobility assessment system for demented
people is presented in this paper. The grade of mobility is measured by means of the person’s pose and
movements in a monitored area. For this purpose, pose estimation and movement detection algorithms have
been developed. These process 3-D data, which are provided by an optical stereo sensor installed in a living
environment. In order to train and test a discriminative classifier a variety of labelled training and test data
was recorded. Moreover, we designed a discriminative and universal feature vector for pose estimation. The
experiments
demonstrated that the algorithms work robustly. In connection with a human machine interface,
the system facilitates a mobilisation as well as a more valid assessment of the patient’s medical condition than
it is presently the case.
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