Abstract
This paper describes an auto-surveillance system which tracks a person who comes in/out an office using multiple camera system. Furthermore it automatically recognize whether the person bring an object in/out. For this purpose, we set three steps. The first step is detecting a person using MBM(Multiple Background Model) and TMB(Temporal Median Background). The second step is calculation of correspondence between persons detected by different view-point cameras in the multiple camera system. We simply calculate the correspondence based on the principal axis and homography. The last step is generating global color model, which includes every local color model organized by GMM (Gaussian Mixture Model) from each camera, of the person. The global color model represented by GMM checks the temporally varied error and detects the object to bring in or out objects. In the experiment, we show the detected human silhouette by background subtraction and the tracking result by correspondence of multiple views. We also show the color segmentation using GMM and the recognition result for detecting objects brought in/out by the tracked person.
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Kim, T., Seo, DW., Chae, HU., Jo, KH. (2009). Auto-surveillance for Object to Bring In/Out Using Multiple Camera. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_65
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DOI: https://doi.org/10.1007/978-3-642-04070-2_65
Publisher Name: Springer, Berlin, Heidelberg
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