Human posture recognition: methodology and implementation
Human posture recognition is an attractive and challenging topic in computer vision due to its promising applications in the areas of personal health care, environmental awareness, human- computer-interaction and surveillance systems. Human posture recognition in video sequences consists of two stag...
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The Korean Institute of Electrical Engineers
2015
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| Online Access: | http://irep.iium.edu.my/43103/ http://irep.iium.edu.my/43103/ http://irep.iium.edu.my/43103/ http://irep.iium.edu.my/43103/1/Human_Posture_Recognition_-_methodology_and_Implementation.pdf |
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eprints |
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iium-431032017-11-15T01:40:27Z http://irep.iium.edu.my/43103/ Human posture recognition: methodology and implementation Htike, Kyaw Kyaw Khalifa, Othman Omran T Technology (General) Human posture recognition is an attractive and challenging topic in computer vision due to its promising applications in the areas of personal health care, environmental awareness, human- computer-interaction and surveillance systems. Human posture recognition in video sequences consists of two stages: the first stage is training and evaluation and the second is deployment. In the first stage, the system is trained and evaluated using datasets of human postures to ‘teach’ the system to classify human postures for any future inputs. When the training and evaluation process is deemed satisfactory as measured by recognition rates, the trained system is then deployed to recognize human postures in any input video sequence. Different classifiers were used in the training such as Multilayer Perceptron Feedforward Neural networks, Self-Organizing Maps, Fuzzy C Means and K Means. Results show that supervised learning classifiers tend to perform better than unsupervised classifiers for the case of human posture recognition. The Korean Institute of Electrical Engineers 2015 Article PeerReviewed application/pdf en http://irep.iium.edu.my/43103/1/Human_Posture_Recognition_-_methodology_and_Implementation.pdf Htike, Kyaw Kyaw and Khalifa, Othman Omran (2015) Human posture recognition: methodology and implementation. Journal of Electrical Engineering Technology, 10 (4). pp. 1911-1915. ISSN 2093-7423 http://www.jeet.or.kr/LTKPSWeb/pub/currentissue.aspx http://dx.doi.org/10.5370/JEET.2015.10.4.1911 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English |
| topic |
T Technology (General) |
| spellingShingle |
T Technology (General) Htike, Kyaw Kyaw Khalifa, Othman Omran Human posture recognition: methodology and implementation |
| description |
Human posture recognition is an attractive and challenging topic in computer vision due to its promising applications in the areas of personal health care, environmental awareness, human- computer-interaction and surveillance systems. Human posture recognition in video sequences consists of two stages: the first stage is training and evaluation and the second is deployment. In the first stage, the system is trained and evaluated using datasets of human postures to ‘teach’ the system to classify human postures for any future inputs. When the training and evaluation process is deemed satisfactory as measured by recognition rates, the trained system is then deployed to recognize human postures in any input video sequence. Different classifiers were used in the training such as Multilayer Perceptron Feedforward Neural networks, Self-Organizing Maps, Fuzzy C Means and K Means. Results show that supervised learning classifiers tend to perform better than unsupervised classifiers for the case of human posture recognition. |
| format |
Article |
| author |
Htike, Kyaw Kyaw Khalifa, Othman Omran |
| author_facet |
Htike, Kyaw Kyaw Khalifa, Othman Omran |
| author_sort |
Htike, Kyaw Kyaw |
| title |
Human posture recognition: methodology and implementation |
| title_short |
Human posture recognition: methodology and implementation |
| title_full |
Human posture recognition: methodology and implementation |
| title_fullStr |
Human posture recognition: methodology and implementation |
| title_full_unstemmed |
Human posture recognition: methodology and implementation |
| title_sort |
human posture recognition: methodology and implementation |
| publisher |
The Korean Institute of Electrical Engineers |
| publishDate |
2015 |
| url |
http://irep.iium.edu.my/43103/ http://irep.iium.edu.my/43103/ http://irep.iium.edu.my/43103/ http://irep.iium.edu.my/43103/1/Human_Posture_Recognition_-_methodology_and_Implementation.pdf |
| first_indexed |
2023-09-18T21:01:25Z |
| last_indexed |
2023-09-18T21:01:25Z |
| _version_ |
1777410648333877248 |