Work

Chatgpt and Biometrics: an Assessment of Face Recognition, Gender Detection, and Age Estimation Capabilities

Year: 2024

Type: conference-paper

Abstract: This paper explores the application of large language models (LLMs), like ChatGPT, for biometric tasks. We specifically examine the capabilities of ChatGPT in performing biometric-related tasks, with an emphasis on face recognition, gender detection, and age estimation. Since biometrics are considered as sensitive information, ChatGPT avoids answering direct prompts, and thus we crafted a prompting strategy to bypass its safeguard and evaluate the capabilities for biometrics tasks. Our study reveals that ChatGPT recognizes facial identities and differentiates between two facial images with considerable accuracy. Additionally, experimental results demonstrate remarkable performance in gender detection and reasonable accuracy for the age estimation tasks. Our findings shed light on the promising potentials in the application of LLMs and foundation models for biometrics.

Source: Proceedings - International Conference on Image Processing

DOI: 10.1109/icip51287.2024.10647924

Authors: Ahmad Hassanpour, Yasamin Kowsari, Hatef Otroshi Shahreza, Bian Yang, Sébastien Marcel

Institutions: Norwegian University of Science and Technology, Idiap Research Institute

Language: English

Topic: Face recognition and analysis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Horizon 2020 Framework Programme

Awards: G2188020438, G3345895242, G5079885849, G6281504974, G7984235579