Abstract
This paper presents the application of machine learning techniques for acquiring new knowledge in the image tracking process, specifically, in the blobs detection problem, with the objective of improving performance. Data Mining has been applied to the lowest level in the tracking system: blob extraction and detection, in order to decide whether detected blobs correspond to real targets or not. A performance evaluation function has been applied to assess the video surveillance system, with and without Data Mining Filter, and results have been compared.
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Rodríguez, B., Pérez, Ó., García, J., Molina, J.M. (2005). Application of Machine Learning Techniques for Simplifying the Association Problem in a Video Surveillance System. In: Mira, J., Álvarez, J.R. (eds) Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach. IWINAC 2005. Lecture Notes in Computer Science, vol 3562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499305_52
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DOI: https://doi.org/10.1007/11499305_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26319-7
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