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DC Field | Value | Language |
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dc.contributor.author | Bagal, V. C. | - |
dc.contributor.author | Hanpode, Pratik | - |
dc.date.accessioned | 2023-01-03T08:31:58Z | - |
dc.date.available | 2023-01-03T08:31:58Z | - |
dc.date.issued | 2022-09-15 | - |
dc.identifier.issn | 2319-7064 | - |
dc.identifier.uri | http://192.168.3.232:8080/jspui/handle/123456789/3550 | - |
dc.description.abstract | Recognizing human motions is important from security point of view at any level and scenario. As there are plenty of human motions in a fraction of second, so classification of each motion is challenging task in real world. A Human activity Recognition System recognizes the Shapes and or orientation depending on implementation to task the system into per forming some job. Movement is a form of nonverbal information. A person can make numerous movements at a time. The proposed work aims to detect the movement and actions of a person using image detection methodology. Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, healthcare, and human-computer interaction (HCI). The proposed work is suitable to identify objectionable human motions of senior citizen who live alone at home. | en_US |
dc.subject | Human activity | en_US |
dc.subject | Image detection | en_US |
dc.subject | sensing technology | en_US |
dc.subject | feature extraction | en_US |
dc.subject | feature extraction | en_US |
dc.title | Motions Detection of Senior Citizen Using Machine Learning | en_US |
Appears in Collections: | Students publication |
Files in This Item:
File | Description | Size | Format | |
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Motion detection.pdf | 363.39 kB | Unknown | View/Open |
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