题目：Face biometrics: Are there any limits to performance?
报告人：Josef Kittler， Distinguished Professor
英国皇家工程院院士，IEEE Fellow，IAPR Fellow
Centre for Vision, Speech and Signal Processing
University of Surrey, UK 时间：2009年9月20日（星期日）上午10:30-11:30 地点：蒙民伟楼404室 摘要：The main factors considered to be challenging for the face biometric
technology are illumination variation, pose, and the paucity of training data.
Considerable advances have been made to confront these problems over the last
five years, resulting in significant performance improvements that make face
biometrics an attractive proposition for many applications. Measures developed
to tackle these problems will be discussed, with a focus on illumination and
pose, and their beneficial effect demonstrated. 简历：Josef Kittler is a Distinguished Professor of Machine Intelligence and
Director of the Centre for Vision, Speech and Signal Processing at the
University of Surrey. He holds a BA degree in Electrical Engineering, a Ph.D.
in Pattern Recognition and a ScD, all from the University of Cambridge. He has
worked on various theoretical aspects of Pattern Recognition, Image Analysis
and Computer Vision, and on many applications including Image Coding, Image
and Video Database Retrieval and Surveillance. His major contributions to
pattern recognition include the k-nearest neighbour method, feature selection,
and multiple expert fusion. In computer vision, contributions include robust
statistical methods for shape analysis and detection, motion estimation and
segmentation, and image segmentation by thresholding and edge detection. He
has served as a member of the Editorial Board of IEEE Transactions on Pattern
Analysis and Machine Intelligence and currently serves on the Editorial Boards
of Image and Vision Computing, Pattern Recognition Letters, Pattern
Recognition and Artificial Intelligence, Pattern Analysis and Applications.
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