Smart Surveillance system using Gaussian Mixture Model

Authors

  • Nihaal Abdul Baseer School of Computer Science and Engineering, REVA University, Bengaluru, India
  • Mohammed Samiuddin School of Computer Science and Engineering, REVA University, Bengaluru, India
  • MD Imran School of Computer Science and Engineering, REVA University, Bengaluru, India
  • Ankur Deb School of Computer Science and Engineering, REVA University, Bengaluru, India
  • Naveen Chandra Gowda School of Computer Science and Engineering, REVA University, Bengaluru, India

DOI:

https://doi.org/10.5281/zenodo.13933443

Keywords:

Gaussian Mixture Model, Surveillance systems

Abstract

Surveillance systems are in huge demand and at best, a necessity in developed and developing communities. But with the rise in demand, a basic integrated system costs a significant amount. This is my attempt at creating an intruder detection system with the tools that are easily accessible and understanding and choosing between the different approaches to solving this problem. We also look at different ways you can better this to your personal preferences. As is, this is a perfect implementation for a general plug-and-play use case.

References

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Published

2024-10-15

How to Cite

Nihaal Abdul Baseer, Mohammed Samiuddin, MD Imran, Ankur Deb, & Naveen Chandra Gowda. (2024). Smart Surveillance system using Gaussian Mixture Model. International Journal of Human Computations & Intelligence, 3(3), 342–349. https://doi.org/10.5281/zenodo.13933443