Harris corner detector and blob analysis featuers in human activty recognetion
the automated detection and monitoring of human activities have gained increased attention in the last decade due to many video applications. They are playing a central role of behavior analysis of human being, where adequate monitoring can minimize the risk of harm to our society. Although, the...
| Main Authors: | , , , , |
|---|---|
| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2017
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/62660/ http://irep.iium.edu.my/62660/1/62660_Harris%20corner%20detector%20and%20blob%20analysis%20featuers.pdf http://irep.iium.edu.my/62660/7/62660_Harris%20corner%20detector%20and%20blob%20analysis%20featuers_scopus.pdf |
| _version_ | 1848785881276612608 |
|---|---|
| author | Babiker, Mohanad Khalifa, Othman Omran Htike, Kyaw Kyaw Hassan Abdalla Hashim, Aisha Zaharadeen, Muhamed |
| author_facet | Babiker, Mohanad Khalifa, Othman Omran Htike, Kyaw Kyaw Hassan Abdalla Hashim, Aisha Zaharadeen, Muhamed |
| author_sort | Babiker, Mohanad |
| building | IIUM Repository |
| collection | Online Access |
| description | the automated detection and monitoring of human
activities have gained increased attention in the last decade due to
many video applications. They are playing a central role of
behavior analysis of human being, where adequate monitoring
can minimize the risk of harm to our society. Although, the
activities recognition has been studied by many researchers but it
still inaccurate. This because of high similarity between human
joints when its move to perform some activities such as walking,
running and jogging. In this paper, a human activity recognition
system was designed based on features extraction analysis. Two
types of features extractions techniques were used, which are the
basic blob analysis features and Harris corner detector. By
comparing the accuracy of the recognition rate in each technique
through the two scenarios we found that Harris corner detector is
more powerful than the basic blob analysis features because of it
is capable to distinguish between the similar activities in an
accurate manner |
| first_indexed | 2025-11-14T17:00:11Z |
| format | Proceeding Paper |
| id | iium-62660 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:00:11Z |
| publishDate | 2017 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-626602018-11-08T03:33:13Z http://irep.iium.edu.my/62660/ Harris corner detector and blob analysis featuers in human activty recognetion Babiker, Mohanad Khalifa, Othman Omran Htike, Kyaw Kyaw Hassan Abdalla Hashim, Aisha Zaharadeen, Muhamed T Technology (General) the automated detection and monitoring of human activities have gained increased attention in the last decade due to many video applications. They are playing a central role of behavior analysis of human being, where adequate monitoring can minimize the risk of harm to our society. Although, the activities recognition has been studied by many researchers but it still inaccurate. This because of high similarity between human joints when its move to perform some activities such as walking, running and jogging. In this paper, a human activity recognition system was designed based on features extraction analysis. Two types of features extractions techniques were used, which are the basic blob analysis features and Harris corner detector. By comparing the accuracy of the recognition rate in each technique through the two scenarios we found that Harris corner detector is more powerful than the basic blob analysis features because of it is capable to distinguish between the similar activities in an accurate manner IEEE 2017-11-28 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/62660/1/62660_Harris%20corner%20detector%20and%20blob%20analysis%20featuers.pdf application/pdf en http://irep.iium.edu.my/62660/7/62660_Harris%20corner%20detector%20and%20blob%20analysis%20featuers_scopus.pdf Babiker, Mohanad and Khalifa, Othman Omran and Htike, Kyaw Kyaw and Hassan Abdalla Hashim, Aisha and Zaharadeen, Muhamed (2017) Harris corner detector and blob analysis featuers in human activty recognetion. In: 4th IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) 2017, 28th-30th November 2017, Putrajaya, Malaysia. http://doi.org/10.1109/ICSIMA.2017.8312025 10.1109/ICSIMA.2017.8312025 |
| spellingShingle | T Technology (General) Babiker, Mohanad Khalifa, Othman Omran Htike, Kyaw Kyaw Hassan Abdalla Hashim, Aisha Zaharadeen, Muhamed Harris corner detector and blob analysis featuers in human activty recognetion |
| title | Harris corner detector and blob analysis featuers in human activty recognetion |
| title_full | Harris corner detector and blob analysis featuers in human activty recognetion |
| title_fullStr | Harris corner detector and blob analysis featuers in human activty recognetion |
| title_full_unstemmed | Harris corner detector and blob analysis featuers in human activty recognetion |
| title_short | Harris corner detector and blob analysis featuers in human activty recognetion |
| title_sort | harris corner detector and blob analysis featuers in human activty recognetion |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/62660/ http://irep.iium.edu.my/62660/ http://irep.iium.edu.my/62660/ http://irep.iium.edu.my/62660/1/62660_Harris%20corner%20detector%20and%20blob%20analysis%20featuers.pdf http://irep.iium.edu.my/62660/7/62660_Harris%20corner%20detector%20and%20blob%20analysis%20featuers_scopus.pdf |