Application of Machine Learning Techniques for Simplifying the Association Problem in a Video Surveillance System

Springer-Verlag Berlin Heidelberg
Publication Type:
Conference Proceeding
Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach - Lecture Notes In Computer Science Volume 3562 - Proceedings of First International Work-Conference on the Interplay Between Natural and Artificial Computation, 2005, 3562 pp. 509 - 518
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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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