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Yuxing Yang

Discovering anomalies in video sequences.

Email: y.yang60@ncl.ac.uk

Project title

Video-based human tracking and action recognition

Supervisors

Project description

We are detecting whether there are anomaly varieties or actions in video sequences. We are using methods for recognition of human targets.

Methodology and objectives

The basic neural networks in computer vision are:

  • the convolutional neural network
  • the recurrent neural network

The main tasks of action classification are:

  • multiple human tracking
  • human action recognition

Both use a deep neural network. Our research will detect video anomaly detection. We have based the method on a deep convolutional generative adversarial network.

Result

The results can be used in video object or action classification to discover anomalies in video sequences. They can also perform intelligent monitoring in real time.

Interests

Computer Vision. Action Recognition. Anomaly Detection.

Qualifications

MSc in Communication and Signal Processing from Newcastle University