Skip to content

Anamoly Detection using Generative Adversarial Neural Network to prevent human trafficking

Notifications You must be signed in to change notification settings

nischay63/hasiee_humanTrafficking

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

39 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

hasiee_humanTrafficking

Winner of the Hackathon conducted at Tryst IIT-Delhi , 2019

Human Trafficking is one of the major concerns in the society. With the boom in Artificial Intelligence we propose a solution that exploits its high computational power to solve the issue.

Proposed Solutions

We propose a Deep learning based solution which can analyze live feed of the camera in real time and further detect any kind of anamalous activity. Details such as location of the incident can be sent to nearest police stations and hospitals

What is an anamalous activity?

Any activity which differs from a normal activity above a calculated threshold can be marked as anamalous activity. For example - A busy road in delhi can be considered as a normal activity whereas riots or voilent activites on the same roads will be considered anamalous.

Major Challenge

Lack of publically available videos/data on rape, human trafficking etc.

Descriptive Solution

We propose to use Generative Adversarial Nets (GANs) which are trained using normal frames and corresponding optical-flow images in order to learn an internal representation of the scene normality. Since our GANs are trained with only normal data, they are not able to generate abnormal events. At testing time the real data is compared with both the appearance and the motion representations reconstructed by our GANs and abnormal areas are detected by computing local differences.

Run

DCGAN can be run by directly running the script

python dcgan.py

For running Cycle GAN test code running the following command

cd pytorch-CycleGAN-and-pix2pix

python test.py --dataroot ./data/ --name maps_cyclegan --model cycle_gan

Team

Nischay Gupta

Nikhil Iyer

Saurabh Khandelwal

Reference

[1] ABNORMAL EVENT DETECTION IN VIDEOS USING GENERATIVE ADVERSARIAL NETS

[2] Image-to-Image Translation with Conditional Adversarial Networks

About

Anamoly Detection using Generative Adversarial Neural Network to prevent human trafficking

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages