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Face Recognition and Detection with Deep Learning

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Understanding Face Detection Architecture

Computer Vision has become a popular area of research in Machine Learning and Deep Learning. Face Recognition uses computer algorithms to find specific details about a person's face. The data about a particular face called Face Template. Face recognition is the problem of recognizing and checking people in a photograph by their face. It is a task that is performed by humans, even in diverging light and when faces are changed by age or interfered with accessories and facial hair. Nonetheless, it is remained a challenging computer vision obstacle for decades until recently. Deep learning systems are able to leverage very large datasets of faces and learn rich and condensed representations of faces, providing modern models to first perform as-well and later to outperform the face recognition abilities of humans.

Face Detection Processing Architecture

  • Capture face from a photo or a video.
  • Face Recognition reads the geometry of the face including the distance between eyes and forehead to chin.
  • A mathematical formula to compare to a database of known faces.
  • Determine faceprint matching with an image in the Facial Recognition System database.

Challenges for Building Face Detection Platform

  • To build an Automatic System for Attendance.
  • The supervisor marks the attendance manually.
  • To mark attendance the person has to go to the office before visiting a work destination.
  • Perform alteration manually by the supervisor.

Solution Offerings for Face Detection and Object Recognition


Develop an application that marks the attendance of the person automatically by fetching its location using Face Detection and Object Recognition. In the below steps, we will guide you through with the approach that we used to build such, backend application for detection, etc. Let's have a look at below pointers.

Approach for Building the Platform

  • The user will be able to get its attendance marked through an Android Application.
  • The functionality of the Android app is to capture the image and also the location of the user.
  • A new user can also be enrolled using the application.

Backend Application for Detection

  • Download all the useful information from the Android Application like Image and Location.
  • Apply Face Recognition Algorithm on the application on the image to make a comparison with the previously stored image.
  • Apply Object Detection Algorithm in application to check for all the tools that the person needs to carry.

Getting Started with Smart Attendance Management System

Features of Smart Attendance System with Face Detection involves -
  • Automatic single touch attendance system for the employees.
  • Automatic visitor management and access control system.
  • Security system.
  • Crowd counting and footfall estimation systems.
  • Detection and Categorisation of all visitors.
  • Detection of persons in multiple zones.
  • Screening of persons across various geographical areas.
  • Unique Enrollment through Train Feature.
  • Capture Face Image and Get Access
Real-Time Applications of Facial Recognition -
  • Security and Identity Management
  • Retail / Emotion & Sentiment Analysis
  • HealthCare
  • Finance and Authentication
  • Time and Attendance
  • Workforce communication
  • Logistics
  • Location Tracking through GPS
  • Secured Communication between Server and Mobile

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