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Facial Recognition For Everyone – A comprehensive guide

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Since the 1970s we are trying to make use of the Facial Recognition system to help us in various things, especially in identification. We all have grown up with watching high tech movies showing the use of Facial Recognition technology to identify the friends or enemies, giving access to some data and now even to unlock our mobile phones. 

We are in the golden age of AI where we want things to work in an advanced way, We are handling issues with much more broaden perspective but sometimes are unable to adapt to these changes at the organisational level. We at DataToBiz are bridging this gap and brings you Facial Recognition for Everyone, Where companies can easily incorporate the power of AI with their current infrastructure. 

Facial Recognition now a day is widely used in Identification and during this time of an epidemic we can easily avoid touching those fingerprint sensor to mark attendance, We bring out Facial Recognition Solutions where we can mark attendance in your very own device. Our Product AttendanceBro comes with API level integration which enables marking attendance from one’s computer after analysing face and some specific factors.

But sometime we might not have an internet connection and want an attendance system that can work on our phone without internet, So here we bring AttendanceBro for Android devices which can work online as well as offline.

Here’s our guide on how to build an attendance system which uses Artificial Intelligence to mark attendance of users offline in Android devices :

Step 1 : Choosing the right model

We at DataToBiz has experienced team which provides AI solution to companies according to the use case. Selecting a model depends on various factors like Number of Users, Nationality, Type of device etc. To know more about selecting a model, feel free to contact us or book an appointment with our AI experts

Step 2 : Adding User to Database

We will be extensively using google’s ml-vision library to process the model offline in the device. First, we need to make an interface to select the image.

Now after making a simple layout of the app, we need to modify the backend of the app.
First, we will create a function which will help us getting Image after pressing “Add a Person” button. Then we have to follow few steps to process the image.

1. Feeding our image to a face detector. Here we will first find the face of the person then use those coordinates to crop it out and pass it to the next step.

2. Preprocess the cropped image, perform mean scaling, convert it into a buffer array and extend its dimension so it can be fed to the classifier.

3. Pass processed Image to classifier and hold the result in a variable.

Then admin can enter the name of the person and save it in the SQL database which will remain in the android device or can be uploaded to server if needed.

Now let’s move to next step of using Face recognition to mark attendance.

Step 3 : Marking Group Attendance

There might be a situation where we need to mark attendance for 1, 2 or 3 users together. Here we bring Group Attendance option which can mark attendance of N person (If they are clearly visible).

  1. Select the image from Camera or gallery.
  2. Preprocess image for detection, and find all the faces in the image.
  3. Pass each face one by one to our preprocess function and get faces ready for our classifier.
  4. Pass the Buffer array to the classifier and compare the results with already stored values in our database.
  5. Show the output of our process on the screen and mark attendance in background.

Take a look at over all structure of the app.

Bonus Step : Liveness Detection

If you look at the app structure you’ll notice that along with Add a Person and Group Attendance there’s another option Live Attendance.
In facial Recognition the main issue we encounter sometimes is spoofing where an intruder uses a photograph of the user to gain access. So here we bring an anti-spoofing way to mark attendance where a user will have to go through a Liveness Detection process where he will be asked to perform a certain task such as blinking an eye or saying a particular word to mark his attendance.

We at DataToBiz are constantly working in utilising the power of Artificial Intelligence in our lives to transform the way we look at problems. We are working deeply in the field of Computer Vision, Data Analysis, Data Warehousing and Data Science.

If you have any query, feel free to email us at or leave a comment.


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