Real-Time Video Analysis for Automated Attendance: An Amazon Web Service Solution
Faculty Mentor
Yun Tian
Document Type
Poster
Start Date
10-5-2023 9:00 AM
End Date
10-5-2023 10:45 AM
Location
PUB NCR
Department
Computer Science
Abstract
This Amazon Web Service program utilizes AWS Kinesis Video and Data Services along with AWS Rekognition for real-time analysis of live video feeds, specifically for detecting and recognizing faces. The program aims to address the potential use case of classroom attendance taking, where live video feeds of the classroom can be analyzed to identify the faces of students present and automatically record their attendance. The program offers a scalable and cost-effective solution for attendance management in classrooms of various sizes, allowing for efficient record keeping while minimizing the need for manual labor. With its real-time video analysis capabilities and customizable features, this program has the potential to streamline attendance management in a variety of educational settings.
Recommended Citation
McGillicuddy, Jake, "Real-Time Video Analysis for Automated Attendance: An Amazon Web Service Solution" (2023). 2023 Symposium. 44.
https://dc.ewu.edu/srcw_2023/res_2023/p1_2023/44
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Real-Time Video Analysis for Automated Attendance: An Amazon Web Service Solution
PUB NCR
This Amazon Web Service program utilizes AWS Kinesis Video and Data Services along with AWS Rekognition for real-time analysis of live video feeds, specifically for detecting and recognizing faces. The program aims to address the potential use case of classroom attendance taking, where live video feeds of the classroom can be analyzed to identify the faces of students present and automatically record their attendance. The program offers a scalable and cost-effective solution for attendance management in classrooms of various sizes, allowing for efficient record keeping while minimizing the need for manual labor. With its real-time video analysis capabilities and customizable features, this program has the potential to streamline attendance management in a variety of educational settings.