
Honors Theses and Capstones
Date of Award
Spring 2025
Project Type
Senior Honors Thesis
College or School
CEPS
Department
Computer Science
Program or Major
Computer Science
Degree Name
Bachelor of Science
First Advisor
Momotaz Begum
Abstract
Facial recognition "in the wild" has posed a challenge in the field of computer vision. Though facial recognition algorithms are generally proficient at recognizing faces up close, subjects at awkward angles and greater distances from the camera make monitoring areas with this software a practical challenge. At UNH's Cognitive Assistive Robotics Lab (CARL), overcoming the weak areas of face recognition is essential to the task of home monitoring. The CARL research team is implementing a suite of robotics and computer vision technologies to monitor patients with Alzheimer's dementia in their homes. This necessitates a reliable and effective facial recognition pipeline capable of distinguishing subjects of interest. My work establishes a framework for evaluating and comparing the performance of such facial recognition pipelines. Furthermore, it explores potential solutions to the shortcomings of existing facial recognition strategies by introducing custom algorithms centered on footage transformations and enhanced face datasets.
Recommended Citation
Bernich, Nathaniel F., "Design and Analysis of Facial Recognition Algorithms for Home Monitoring" (2025). Honors Theses and Capstones. 912.
https://scholars.unh.edu/honors/912