MSPA-MCS: Face Recognition Using Integral Invariants and Cryptology

MSPA-MCS：使用积分不变量和密码学进行人脸识别

• 批准号: 0434355
• 负责人: Nigel Boston
• 金额: $ 50万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-15 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0434355&HistoricalAwards=false
• 关键词: MSPA; MCS; Face; Recognition; Using

The fundamental technical challenge of human face recognition is to deal with the extremely broad range of variations in a face's appearance due to pose, lighting, age, facial expression, distance and other factors. Ideal facial features should remain invariant under these variations. While current face recognition methods are limited in the conditions where they work, recent advances in the mathematical theory of invariants and recent connections forged with cryptology provide new insights for the face recognition problem that may help broaden the generality and robustness of face recognition systems. In this project, an interdisciplinary team will explore a unique approach that brings together the latest developments in the mathematics of integral invariants, psychophysical experiments on face recognition by humans, and state-of-the-art face recognition algorithms and system development.Specifically, we plan to address the following research goals:Establish a common mathematical foundation between cryptology and object recognition, in particular obtaining information-theoretical limits to data compression of human facesInvestigate the mathematical theory of integral invariants for 3D geometrical objects, and develop efficient invariant feature extraction and pattern recognition algorithms Interact with a professional cartoonist and use experimental psychophysical evidence to assess perceptual significance and to explore biological interpretations of mathematical 3D integral invariant features in the context of human face recognitionDevelop a prototype system implementation for 3D moving face recognition. In particular, we will focus on a scenario with multiple camera in a semi-controlled environment for access control and watch-list spotting applicationsThe approaches taken in this project are cutting-edge, unconventional, and promise significant breakthrough in advancing both the theory and practice of face recognition performance. Broad ImpactsIn this project we plan to hold a summer research experience program to serve under-represented groups; to develop a new biometric informatics class that involves undergraduate students in developing parts of prototype face recognition systems; to hold a man-machine face recognition contest to garner public awareness of this area and to attract young people to science and technology. Specifically, in both laboratories and courses we will foster an environment for students from both mathematics and computer science backgrounds to interact in learning and research, to stimulate new ideas and to appreciate the mutual impact and interactions between mathematics and computer science.

人脸识别的根本技术挑战是处理由于姿势、光照、年龄、面部表情、距离等因素导致的人脸外观的极大范围的变化。理想的面部特征应该在这些变化下保持不变。虽然目前的人脸识别方法在它们工作的条件下是有限的，但不变量数学理论的最新进展和最近利用密码学建立的联系为人脸识别问题提供了新的见解，这可能有助于拓宽人脸识别系统的通用性和健壮性。在这个项目中，一个跨学科的团队将探索一种独特的方法，它结合了积分不变量数学的最新发展，人类人脸识别的心理物理实验，以及最先进的人脸识别算法和系统开发。具体地说，我们计划解决以下研究目标：在密码学和对象识别之间建立共同的数学基础，特别是获得人脸数据压缩的信息理论限制研究3D几何对象的积分不变量的数学理论，并开发了高效的不变特征提取和模式识别算法，与专业漫画家互动，使用实验的心理物理证据来评估感知意义，并在人脸识别的背景下探索数学3D积分不变特征的生物解释。特别是，我们将专注于在半控制环境中使用多个摄像头的场景，用于访问控制和监视名单识别应用程序。本项目所采用的方法是尖端的、非常规的，有望在推进人脸识别性能的理论和实践方面取得重大突破。广泛影响在这个项目中，我们计划举办暑期研究体验计划，为代表不足的群体提供服务；开发一个新的生物特征信息学课程，让本科生参与开发人脸识别系统原型的部分；举办人机人脸识别比赛，以提高公众对这一领域的认识，并吸引年轻人投身于科学和技术领域。具体地说，在实验室和课程中，我们将为具有数学和计算机科学背景的学生创造一个环境，让他们在学习和研究中互动，激发新想法，并欣赏数学和计算机科学之间的相互影响和互动。