Anomaly detection in engineering systems is cast as a problem of detecting outliers to the distribution of observations representing a state of normality. We focus on anomaly detection in machine perception. We argue that in addition to outlier detection, anomaly detection in machine perception systems requires other detection mechanisms. They include incongruence detection, data quality assessment, decision confidence gauging, and model drift detection. These mechanisms are elaborated and their application illustrated on a problem of anomaly detection in a sports video interpretation system.

 

Professor Josef Kittler FREng heads the Department of Electronics in the Faculty of Engineering and Physical Sciences. He received his BA, PhD and DSc degrees from the University of Cambridge. He joined the University of Surrey in 1986, after spending 5 years with EPSRC Rutherford Appleton Laboratory, and before that, conducting research on personal fellowships at Cambridge, Oxford, Southampton, and ENST Paris. He founded the Centre for Vision, Speech and Signal Processing, which now has over 100 researchers. He teaches and conducts research in Signal Processing and Machine Intelligence, with a focus on Biometrics, and Cognitive Vision. He published a Prentice Hall textbook on Pattern Recognition: A Statistical Approach, and more than 700 scientific papers. He is Series Editor of Springer Lecture Notes on Computer Science. He served as President of the International Association for Pattern Recognition 1994-1996. In 2006 he was awarded the KS Fu Prize from the International Association, for outstanding contributions to pattern recognition. He received Honorary Doctorates from the University of Lappenranta in 1999 and the Czech Technical University in Prague in 2007. In 2008 he was awarded the IET Faraday Medal and in 2009 he became EURASIP Fellow. He is a co-founder of OmniPerception Ltd.