Human Detection and Tracking in Surveillance Areas

This project "Human Detection in Surveillance Areas" was assigned to Bennett University by Bharat Electronics Limited (BEL) and I completed this project under the excellent guidance of Dr. Vipul Kumar Mishra . The task was to detect any human or vehicle activity in restricted areas and surveillance zones at both daytime and night-time using RGB and IR cameras respectively.

I worked closely with deep learning based object detection models to detect human presence. As our final dataset (after many changes and additions) was really huge (around ~42 GB), it was not possible to train on local machines. Our team tried training on Google Cloud Platform (GCP) but for some reason was not able to get any GPU quota and CPU instances were taking lot of time. Then, we actually trained on DGX V-100 supercomputer remotely using multiple GPUs for super fast training speed. We were able to achieve good results on our custom dataset.

Sample predictions

Please note that the below images are not part of the original dataset but are taken from publically available web images (source) and then our ML algorithm is run to detect humans/vehicles. Abiding by the terms of NDA, I cannot disclose any information about models, datasets or reports.

soldier prediction image 1
soldier prediction image 2
soldier prediction image 1
soldier prediction image 2

AfterMaths

Our team completed this project just in time before the deadline. Here are some learnings from the project:

Conclusion

I really enjoyed working on this project with the team. Special thanks to Dr. Vipul Kumar Mishra for providing this opportunity. Defense systems such as this project can also be applied in other physical security areas like entry points, malls, banks, etc. I would love to get more knowledge about leveraging AI in defense and security, contact me.