Space-time templates based features for patient activity recognition
Joint Authors
Abbas, Muhammad Adil
Murtada, Faizah
Yusuf, Muhammad Harun
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 4 (31 Jul. 2021), pp.504-512, 9 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-07-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Abstract EN
Human activity recognition has been the popular area of research among the computer vision researchers.
The proposed work is focused on patient activity recognition in hospital room environment.
We have investigated the optimum supportive features for the patient activity recognition problem.
Exploiting the strength of space-time template approaches for activity analysis, Motion-Density Image (MDI) is proposed for patient’s activities when used supportively with Motion-History Image (MHI).
The final feature vector is created by combining the description of MHI and MDI using Motion Orientation Histograms (MOH) and then applying Linear Discriminant Analysis (LDA) for dimensionality reduction.
The LDA technique not only reduced the complexity cost required for classification but also played vital role to get best recognition results by increasing between-class separation and decreasing the with-in class variance.
To validate the proposed approach, we recorded a video dataset containing 8 activities of patients performed in hospital room environment under indoor conditions.
We have successfully validated the results of the proposed approach on our dataset by training the SVM classifier and achieved 97.9% average recognition accuracy.
American Psychological Association (APA)
Abbas, Muhammad Adil& Murtada, Faizah& al-Mustadi, Muhammad Salih Ubayd Allah& Yusuf, Muhammad Harun. 2021. Space-time templates based features for patient activity recognition. The International Arab Journal of Information Technology،Vol. 18, no. 4, pp.504-512.
https://search.emarefa.net/detail/BIM-1434298
Modern Language Association (MLA)
al-Mustadi, Muhammad Salih Ubayd Allah…[et al.]. Space-time templates based features for patient activity recognition. The International Arab Journal of Information Technology Vol. 18, no. 4 (Jul. 2021), pp.504-512.
https://search.emarefa.net/detail/BIM-1434298
American Medical Association (AMA)
Abbas, Muhammad Adil& Murtada, Faizah& al-Mustadi, Muhammad Salih Ubayd Allah& Yusuf, Muhammad Harun. Space-time templates based features for patient activity recognition. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 4, pp.504-512.
https://search.emarefa.net/detail/BIM-1434298
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 510-511
Record ID
BIM-1434298