MAKER: Facial feature detection library for teaching algorithm basics in python

American Society for Engineering Education, 2018. This paper describes an approach to teach face detection algorithms to beginner level programming learners using a face detection tool built in Python. Learners are expected to understand and practice their Python coding skills and algorithm knowledge in a facial feature detection and image processing application. This project is a Science Technology Engineering and Math (STEM) extensive module and includes research analysis and activity components. Existing work focuses on teaching algorithms to students using interactive tools and games [3,4,7]. This work lets students learn face detection algorithms using a library. Furthermore, students learn how to use the Dlib, Yattag, Cv, Numpy, Tkinter classes in Python along with the algorithmic details. This application enriches school curriculum by adding machine/software interactions and digital image processing. After completing the module activities, students are evaluated on basic understanding of face detection applications, computer vision, and the ability to complete the programming tasks. This classroom model has been implemented in a high school computer science class to provide an interesting way to help students learn programming and to motivate students to learn more about computer science.

MAKER: Facial feature detection library for teaching algorithm basics in python Conference Paper