Title

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.

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May 10th, 9:00 AM May 10th, 10:45 AM

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.