This paper is published in Volume-5, Issue-2, 2019
Area
Face Recognition
Author
Prasad Laxman Salokhe, Ravi Raj, Sampreet U. Gaonkar, Shalini
Org/Univ
Sai Vidya Institute of Technology, Bengaluru, Karnataka, India
Pub. Date
30 April, 2019
Paper ID
V5I2-2109
Publisher
Keywords
Face recognition, Machine learning model

Citationsacebook

IEEE
Prasad Laxman Salokhe, Ravi Raj, Sampreet U. Gaonkar, Shalini. Criminal face recognition using video surveillance, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Prasad Laxman Salokhe, Ravi Raj, Sampreet U. Gaonkar, Shalini (2019). Criminal face recognition using video surveillance. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Prasad Laxman Salokhe, Ravi Raj, Sampreet U. Gaonkar, Shalini. "Criminal face recognition using video surveillance." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

Due to a rise in criminal activities, the identification of the criminals takes a lot of time even if the person is a recidivist. To identify and track missing or trafficked people the time taken to identify and save them may very well be greater before the person disappears again. To overcome this we propose a system that is highly reliable to recognize these people using face recognition techniques to recognize them anywhere in real time using CCTV or other video provided device so that actions could be taken more quickly. We move the whole system to the cloud so that the pictures of these individuals can be uploaded to train the face recognition model and can be used by many law agencies. The pictures can be uploaded from a local computer that is connected to the model on cloud and the database will be updated by adding the uploaded pictures. The processing also takes place in the cloud hence reduces the load on the local computer and only the results are sent back. Our proposed system yields much better processing and response speed and results in centralizing the whole data which can be updated and used by anyone without lowering the local systems performance.