GhostNet: An intelligent anomaly detection agent
Overview:
Rapid expansion of metro cities has given rise to security concerns and has resulted in increased need of intelligent CCTV cameras to ensure the safety of people. The activity recognition of videos is a complex process. We have came up with an approach to tackle the security issue with deep neural networks.
Problem Statement:
We need to address the manual monitoring of CCTV cameras around a metro city and replace it with more robust and automated solution such as some intelligent anomaly detection agent.
Objective:
The main and prime objective for this project is to help locate the anomalous event. To achieve that , we need to train the 3D neural network model. This will help authorities to cop up against the crimes and incidents happening around the city.
Challenges:
There is a negligible borderline between normal and abnormal activities. The same normal event can be represented as abnormal activity under certain conditions such as crowded scene.
The abnormal actions vary form place to place and region to region , so the dataset needs to be diverse.
The point to view for a cameras is a contributing factor for correct anomaly detection.
There is always a possibility of noise in data , which ultimately leads to wrong predictions.
Tools and Technologies:
Tools and technologies that will be used for this project, but might not limited to, include:
Software Technologies and Frameworks:
For deep neural network:
NVIDIA Deepstream
NVIDIA CUDA
Tensorflow
PyTorch
OpenCV
Google Colab
Linux
Virtual environments
3D and 2D CNN or RNN
For Web and Mobile Interfaces (UI):
Flask
Node.js
Angular.js
Bootstrap
NoSQL/MySQL
Google cloud
Heroku/AWS EC2 / AWS ELB
Demo Videos:
Dr. Zeeshan Gilani
Supervisor
Assistant Professor, Computer Science
Area of Interest:
Machine Learning
Image processing
Data mining
Biological network and medical Imaging
Dr. Usama Bajwa
Co-supervisor
Co-PI, Video Analytics lab, National Centre in Big Data and Cloud Computing
Program Chair (FIT 2019)
HEC Approved PhD Supervisor,
Assistant Professor & Associate Head of Department
Department of Computer Science , COMSATS University Islamabad, Lahore Campus, Pakistan
www.usamaijaz.comwww.fit.edu.pkJob ProfileGoogle Scholar Profile