Pattern classification of human interactions from videos / Muhsin Abdul Mohammed
The objective of this research project is to build a machine learning model to classify human interactions from a stream of video. Being able to classify human interaction from videos is essential in the development of robotic assistance systems, video annotation, surveillance systems and many m...
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| Format: | Thesis |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/9627/1/Muhsin_Abdul_Mohammed.jpg http://studentsrepo.um.edu.my/9627/8/muhsin.pdf http://studentsrepo.um.edu.my/9627/ |
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| Summary: | The objective of this research project is to build a machine learning
model to classify human interactions from a stream of video. Being
able to classify human interaction from videos is essential in the
development of robotic assistance systems, video annotation,
surveillance systems and many more applications. It is necessary that
the algorithm performing this task needs to be robust and only relies on
monocular vision systems.
In order to build a classifier capable of achieving this task, the
machine learning model needs to be able to learn spatial and temporal
patterns from the videos. A cascaded architecture of Convolutional
Neural Networks and Recurrent Neural Networks have been created to
achieve this task in this research. There have been investigations made
to identify the best spatial and temporal architectures that would give
the optimal result. |
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