Utilizing Facial Recognition Software to Record Classroom Attendance

Abstract

Facial recognition software offers many opportunities for educators, especially in regards to recording classroom attendance. With so much time lost in the classroom each day, utilizing facial recognition software allows professors to reclaim that lost time, and, therefore, accomplish more in the classroom. In practice, this technology is relatively new. Within the past few decades advancements have been made to introduce facial recognition techniques to the general public. The majority of the research has been initiated by the intelligence community to track persons of interest. However, these practices have become common with various businesses and even churches. Corporations, such as Amazon and Microsoft, have taken this opportunity to provide customers with access to servers and APIs that allow individuals to incorporate facial recognition software in their own personal lives or for their businesses. There are also those who have elected to create their own facial recognition programs by using libraries, such as OpenCV. Combining the latter method with proper software process procedures has produced a program that is intended to aid professors in the classroom in regards to recording classroom attendance. Because of the litany of tools and libraries required to use facial recognition software, operating these programs within a separate preconfigured virtual environment is likely the best practice. Ubuntu has proven to be the best choice thus far. Using a process most similar to Scrum, this software was developed by utilizing multiple iterations in the form of weekly sprints. After detailing the creation of this software and validating that the solution works as expected, one should gain insight into the inner workings of facial recognition software. The result should fill the needs of school faculty and allow for future researchers to further optimize this technology to enhance its performance and efficiency.