We propose a robust method to extract silhouettes of foreground objects from color video sequences. To cope with various changes in the background, the background is modeled as generalized Gaussian Family of distributions and updated by the selective running average and static pixel observation. All pixels in the input video image are classified into four initial regions using background subtraction with multiple thresholds, after which shadow regions are eliminated using color components. The final foreground silhouette is extracted by refining the initial region using morphological processes. We have verified that the proposed algorithm works very well in various background and foreground situations through experiments. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kim, H., Sakamoto, R., Kitahara, I., Toriyama, T., & Kogure, K. (2007). Robust foreground extraction technique using Gaussian Family model and multiple thresholds. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4843 LNCS, pp. 758–768). Springer Verlag. https://doi.org/10.1007/978-3-540-76386-4_72
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