Unique Registration Number: GSInC-I-000300
Innovator Name:
Manobhav Sachan
Teja Siva Narayana
Deepak S
Name of a Mentor:- E. Mallikarjun
Name of School/College/Startup/Organisation: National Institute of Technology Goa
Contact No: +917559382613
Contact Email: manobhavsachan@gmail.com
Project Objective:
To create a app which can be used to take group photo and mark attendance using ML Models to provide excel report.
Abstract:
- This project introduces an innovative automated attendance system tailored for educational institutions, leveraging advanced machine learning algorithms to identify and record student attendance from group photos. Addressing the inefficiencies and inaccuracies associated with manual attendance processes, our system employs computer vision techniques and integrates Deep Face, a cutting-edge face recognition library. The methodology of the system encompasses three crucial steps: face detection, feature extraction, and attendance recognition. By seamlessly integrating these processes, our solution ensures precise attendance recording while significantly reducing the time and effort traditionally required for manual attendance management. The proposed system utilizes the hear cascade algorithm for efficient face detection within group photos. Subsequently, Deep Face, a powerful machine-learning library, is employed to extract and analyze the distinctive facial features of each identified face. In the final step, the system compares these extracted features with a high-definition database of classroom student photos, enabling accurate recognition and automated attendance marking for every student present in the photo. This three-step approach guarantees a comprehensive and accurate automated recording of student attendance, offering a transformative solution to streamline attendance management processes and enhance the overall efficiency of educational institutions.
Project Outcome/result/findings:
We were able to successfully make an app which can to the group attendance task. The maximum no. of people our app was capable of was in range of 40 to 50 with HD photo.
Innovative Approach:
- An app which can mark attendance from group photo was implemented for the first time. We implemented a PWA app which works on website, android and iOS all. The size of PWA app is also in range of 500 kB making it more optimised and easy to use on all device types.