collaborators

6 papers

cs.CV2021

Compact CNN Models for On-device Ocular-based User Recognition in Mobile Devices

Ali Almadan, Ajita Rattani

A number of studies have demonstrated the efficacy of deep learning convolutional neural network (CNN) models for ocular-based user recognition in mobile devices. However, these hi…

cs.CV2021

Investigating Fairness of Ocular Biometrics Among Young, Middle-Aged, and Older Adults

Anoop Krishnan, Ali Almadan, Ajita Rattani

A number of studies suggest bias of the face biometrics, i.e., face recognition and soft-biometric estimation methods, across gender, race, and age groups. There is a recent urge t…

cs.CV2021

Towards On-Device Face Recognition in Body-worn Cameras

Ali Almadan, Ajita Rattani

Face recognition technology related to recognizing identities is widely adopted in intelligence gathering, law enforcement, surveillance, and consumer applications. Recently, this…

cs.CV2020

Probing Fairness of Mobile Ocular Biometrics Methods Across Gender on VISOB 2.0 Dataset

Anoop Krishnan, Ali Almadan, Ajita Rattani

Recent research has questioned the fairness of face-based recognition and attribute classification methods (such as gender and race) for dark-skinned people and women. Ocular biome…

cs.CV2020

Understanding Fairness of Gender Classification Algorithms Across Gender-Race Groups

Anoop Krishnan, Ali Almadan, Ajita Rattani

Automated gender classification has important applications in many domains, such as demographic research, law enforcement, online advertising, as well as human-computer interaction…

cs.CV2020

BWCFace: Open-set Face Recognition using Body-worn Camera

Ali Almadan, Anoop Krishnan, Ajita Rattani

With computer vision reaching an inflection point in the past decade, face recognition technology has become pervasive in policing, intelligence gathering, and consumer application…