Face recognition is a identification of humans by the unique characteristics of their faces. This is the fastest bio-metric technology. This technology is used to control,track and monitor individual students of a class. This can detect faces in images,quantify their features,and then match them against stored templates in a database. This reduces wastage of time and differentiate faces from non-faces so that errors can be minimized.

Pre-requisites/Implementation Technologies

1 . Opencv
2 . Basics about Python
3 . LBPH recognizer
1 . Python
2 . Html5, CSS3, Bootstrap
3 . LBPH recognizer
4 . Haar Cascade
1 . Camera - 1
2 . Raspberry pi

Note: One kit will be provided per team for practice.

Project Development Lifecycle

Day Action plan Detailed Plan
Day 1 Project Analysis 1. Explanation about Project Development Cycle.
2. Project Requirements.
3. Introduction to project and basic functionality.
Day 2 Gathering Data Gather face data of the person you want to recognize
Day 3 Coding 1. Write a code on python using opencv
2. Compare Images
Day 4 Designing Designing the template
Day 5 Face Recognition Feed new faces of the persons & see if the face recognizer is recognizing or not.
Day 6 Testing and Documentation 1. Testing for any bugs and issues.
2. Preparing the documentation of the project

Team Size and Price

Team Size Price for Team
4 4000

Note: A team can have maximum of 4 members.

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