Using Real-time Facial Recognition for Vehicle Driver Authentication

随着传感器技术、机器学习、处理能力和互联网接入的进步，智能汽车正在迅速成为现实。随着车辆等智能设备和环境的进步和普及，安全和身份验证的健壮性和可靠性变得越来越重要。人脸识别用于司机身份验证是一种真正的可能性，需要进一步研究、微调和测试。在这个项目中，我们的目标是解决一些与智能车辆中用于驾驶员身份验证的面部识别相关的重要研究问题。这些问题包括：i)确定可靠和稳健地执行手头任务所需的最小数目、方向和摄像机设置；ii)开发能够用最少的训练样本、在具有挑战性的条件下以及随着时间的变化而识别和认证人脸的稳健模型；iii)确定重新识别(短期)以及重新培训(长期)的最佳时间；以及iv)用户对这种技术的感觉和交互。该项目将培养一名博士后研究员、一名博士生和两名硕士研究生。这项工作的主要受益者将是爱迪德加拿大公司，它是一家国际软件和安全公司在加拿大的分支机构。该公司将立即采取措施，将这项技术产品化和商业化，目前的客户已经表现出了兴趣。此外，近年来，加拿大已经成为人工智能和机器学习领域的全球领先者，这已经带来了显著的经济效益和增长。该项目将通过在图像处理和安全领域开发新的算法和智能系统，为加拿大的人工智能生态系统做出贡献。

Smart vehicles are rapidly becoming a reality with advances in sensor technologies, machine learning, processing power, and internet access. With advances and popularization of intelligent devices and environments such as vehicles, it is increasingly critical that security and authentication be robust and reliable. Facial recognition for authentication of drivers is a real possibility that needs to be further studied, fine-tuned, and tested. In this project, we aim to tackle a number of important research questions associated with facial recognition for driver authentication in smart vehicles. These questions include i) identifying the minimum number, orientation, and setup of cameras required to reliably and robustly perform the task at hand, ii) developing robust models capable of recognizing and authenticating human faces with minimal training samples, under challenging conditions, and with changes over time, iii) identifying the optimum time for re-identification (short-term) as well as re-training (long-term), and iv) how users feel about and interact with this kind of technology. The project will train a postdoctoral fellow, a PhD student, and two master's students. The main beneficiary of this work will be Irdeto Canada, the Canadian arm of an international software and security company. The company will take immediate steps towards productization and commercialization of the technology with current customers having already shown interest. Additionally, in recent years, Canada has emerged as a global leader in artificial intelligence and machine learning, which has already resulted in significant economic benefits and growth. This project will contribute to Canada's AI ecosystem through development of novel algorithms and intelligent systems in the fields of image processing and security.