Abstract
This paper presents a system to monitor a space and detect intruders. Specifically, the system analyzes color video to determine if an intruder entered the space. The system compares any new items in a video frame to a collection of known items (e.g. pets) in order to allow known items to enter and leave the space. Simple trip-line systems using infrared sensors normally fail when a pet wanders into the path of a sensor. This paper details an adaptation of the mean shift algorithm (described by Comaniciu et al.) in RGB color space to discern between intruders and benign environment changes. A refinement to the histogram bin function used in the tracking algorithm is presented which increases the robustness of the algorithm.
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Cermak, G., Keyzer, K. (2007). Unsupervised Intrusion Detection Using Color Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_76
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DOI: https://doi.org/10.1007/978-3-540-76856-2_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76855-5
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