Face Liveness Detection In Face Recognition
24.7 هزار بار بازدید -
3 سال پیش
-
Face Liveness Detection is a
Face Liveness Detection is a technology in face recognition which checks whether the image from the webcam comes from a live person or not. Face Liveness Detection is an essential prerequiste of Face Recognition system.
In face recognition, the identification of an individual is done by comparing the captured images with the stored images of that person in real time. These recognition systems are in the rapid development phase and are accumulated with a new strong algorithm that improves the system day by day. However, these systems are facing many security issues as frauds are increasing on a daily basis and there is a need to upgrade these systems to make them more secure, reliable and automatic. So by observing all these things we are inspired to build our project “Face Antispoofing System” which not only improves the existing system but also adapts to some of the security challenges making this system more secure and reliable.
In this video tutorial, we perform the end to end pipeline for deploying the face antispoofing system by using opencv. First, we train the liveness detection model by using our own dataset and then we deploy the trained model using opencv and python.
Workflow of the system :
At first, the input image is captured by using a webcam and then we apply face detection algorithm to the input image. Then the detected face is forwarded to the liveness net which check whether the image comes from a real person or not.
Github link to the project files : https://github.com/prabhat-123/Face_A...
Dataset link : https://drive.google.com/drive/u/0/fo...
In face recognition, the identification of an individual is done by comparing the captured images with the stored images of that person in real time. These recognition systems are in the rapid development phase and are accumulated with a new strong algorithm that improves the system day by day. However, these systems are facing many security issues as frauds are increasing on a daily basis and there is a need to upgrade these systems to make them more secure, reliable and automatic. So by observing all these things we are inspired to build our project “Face Antispoofing System” which not only improves the existing system but also adapts to some of the security challenges making this system more secure and reliable.
In this video tutorial, we perform the end to end pipeline for deploying the face antispoofing system by using opencv. First, we train the liveness detection model by using our own dataset and then we deploy the trained model using opencv and python.
Workflow of the system :
At first, the input image is captured by using a webcam and then we apply face detection algorithm to the input image. Then the detected face is forwarded to the liveness net which check whether the image comes from a real person or not.
Github link to the project files : https://github.com/prabhat-123/Face_A...
Dataset link : https://drive.google.com/drive/u/0/fo...
3 سال پیش
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