Abstract
Motivation |
During the weeks of final exams, students may feel difficult to find available seats in library to study. As a consequence, students have to waste lots of time finding the seat rather than concentrating on reviewing their courses. This phenomenon motivates us to develop a system to monitor the number of people in rooms and give users access to the data through a web application, which will make life much easier for students or anyone else who would like to stay in libraries.
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Method |
The core of the project is to determine the number of people in certain areas that corresponding to seats. A direct way to realize the goal is to process the data collected from censors, but we decide to use computer vision method to accomplish our project, since all we need is a camera instead of multiple censors. Once the videos or images are captured by the camera, we can use computer vision libraries like OpenCV to analyze the frames we get. |
Process |
After the frames are captured by camera and transmitted to computer, the OpenCV library is used for human detection. Then the number of people detection result is uploaded into AWS DyanmoDB, ready to be used. Finally, we have a webpage to display current library occupancy status to users, including the number of people and the status of individual seat availability. |