Graduation Year
2018
Date of Submission
4-2018
Document Type
Campus Only Senior Thesis
Degree Name
Bachelor of Arts
Department
Computer Science
Reader 1
Alexandra Papoutsaki
Terms of Use & License Information
Rights Information
2018 Alexander PS Clemens
Abstract
Face detection refers to a number of techniques that identify faces in images and videos. As part of the senior project exercise at Pomona College, I explore the process of face detection using a JavaScript library called CLMtrackr. CLMtrackr works in any browser and detects faces within the video stream captured by a webcam. The focus of this paper is to explore the shortcomings in the inclusivity of the CLMtrackr library and consequently that of face detection. In my research, I have used two datasets that contain human faces with diverse backgrounds, in order to assess the accuracy of CLMtrackr. The two datasets are the MUCT and PPB. In addition, I investigate whether skin color is a key factor in determining face detection's success, to ascertain where and why a face might not be recognized within an image. While my research and work produced some inconclusive results due to a small sample size and a couple outliers in my outputs, it is clear that there is a trends toward the CLMtrackr algorithm recognizing faces with lighter skin tones more often than darker ones.
Recommended Citation
Clemens, Alexander, "Investigating the Inclusivity of Face Detection" (2018). CMC Senior Theses. 1836.
https://scholarship.claremont.edu/cmc_theses/1836
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.
