APA 6th Edition Niemann, H., Paulus, D. i Huang, Y. (2000). Background-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation. Journal of computing and information technology, 8 (4), 349-353. https://doi.org/10.2498/cit.2000.04.10
MLA 8th Edition Niemann, Heinrich, et al. "Background-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation." Journal of computing and information technology, vol. 8, br. 4, 2000, str. 349-353. https://doi.org/10.2498/cit.2000.04.10. Citirano 28.02.2021.
Chicago 17th Edition Niemann, Heinrich, Dietrich Paulus i Yu Huang. "Background-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation." Journal of computing and information technology 8, br. 4 (2000): 349-353. https://doi.org/10.2498/cit.2000.04.10
Harvard Niemann, H., Paulus, D., i Huang, Y. (2000). 'Background-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation', Journal of computing and information technology, 8(4), str. 349-353. https://doi.org/10.2498/cit.2000.04.10
Vancouver Niemann H, Paulus D, Huang Y. Background-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation. Journal of computing and information technology [Internet]. 2000 [pristupljeno 28.02.2021.];8(4):349-353. https://doi.org/10.2498/cit.2000.04.10
IEEE H. Niemann, D. Paulus i Y. Huang, "Background-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation", Journal of computing and information technology, vol.8, br. 4, str. 349-353, 2000. [Online]. https://doi.org/10.2498/cit.2000.04.10
Sažetak This paper addresses the problem of image segmentation using motion and luminance information. We use the dominant motion model to calculate both the background and foreground motion in a robust estimation framework and then combine it with the result of static segmentation using the watershed algorithm to segment the foreground from the background. In this paper, the previous pixelbased (or over a small neighborhood) motion measure is replaced by the patch-based motion measure in motion segmentation. Experimental results are given to show the efficiency of our method.