Face Biometrics for Security: Long-Range and Surveillance
This tutorial introduces issues in long-range facial image acquisition and measures for image quality and their usage, as well as subsequent challenges for face recognition. The first several modules on image acquisition for face recognition discuss concerns related to lighting, sensors, and lenses, which impact short-range biometrics, but are more pronounced in long-range biometrics. We then go on to introduce the design of controlled experiments for long-range face recognition and why they are needed. With our experiments, we go on to show some of the weather and atmospheric effects that occur for long-range imaging, with numerous examples. Next, we address measurements of "system quality" including image-quality measures and their use in the prediction of face recognition algorithm performance. That module introduces the concept of post-recognition score analysis and techniques for analyzing different "equality" measures. The last two modules of this tutorial explore long-range face recognition directly. Facial feature detection is an important prerequisite for face recognition, and we look at two different approaches for accurately accomplishing this for long-range scenarios. Finally, we address the very difficult problem of blur "both motion and atmospheric" including common sources in acquisition and algorithms to mitigate its effects.
What you will learn:
- Review motivating concerns over surveillance with biometrics in difficult environments
- Consider lighting, sensor and weather and atmospheric impacts
Related courses:
Who should attend: Electrical engineer, Systems engineer, Hardware engineer, Design engineer, Product engineer, Communication engineer
Instructors
Walter J. Scheirer
Dr. Walter J. Scheirer received his Ph.D. from the University of Colorado and his M.S. and B.A. degrees from Lehigh University, focused in security. He is currently the Director of Research and Development at Securics, Inc. He has published and lectured widely on a variety of security related topics, including face detection for surveillance, privacy enhancing technologies, biometric fusion, secure cryptographic channels, network intrusion detection and Unix system security
Terrance Boult
Dr. Boult is a Professor of Computer Science at the University of Colorado where his role includes working with faculty and local companies to develop and transfer technology in the Springs area. He studied at Columbia University, earning his MS and PhD degrees in computer science. Dr. Boult has published over 150 papers and holds 7 patents, with 9 patents pending. He publishes in Computer Vision/Robotics as well as in Networking and Mobile Computing.
Publication Year: 2010
ISBN: 978-1-4244-6214-8