Honors Theses and Capstones

Date Completed

Spring 2025

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.

First Advisor

Momotaz Begum

College or School

CEPS

Department or Program

Computer Science

Degree Name

Bachelor of Science

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