Abstract
Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three types of detectors for detecting abnormal activity are developed using negative selection. Tracks gathered by people’s movements in a room are used for experimentation and results have shown that the classifier is able to discriminate abnormal from normal activities in terms of both trajectory and time spent at a location.
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© 2004 Springer-Verlag Berlin Heidelberg
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Sasmita, L., Liu, W., Venkatesh, S. (2004). An Immunological Approach to Raising Alarms in Video Surveillance. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30543-9_11
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DOI: https://doi.org/10.1007/978-3-540-30543-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23985-7
Online ISBN: 978-3-540-30543-9
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