IEEE Trans Pattern Anal Mach Intell. 2011 Jul;33(7):1429-41. doi: 10.1109/TPAMI.2010.196. Epub 2010 Nov 18.
In this paper, we present a method for extracting consistent foreground regions when multiple views of a scene are available. We propose a framework that automatically identifies such regions in images under the assumption that, in each image, background and foreground regions present different color properties. To achieve this task, monocular color information is not sufficient and we exploit the spatial consistency constraint that several image projections of the same space region must satisfy. Combining the monocular color consistency constraint with multiview spatial constraints allows us to automatically and simultaneously segment the foreground and background regions in multiview images. In contrast to standard background subtraction methods, the proposed approach does not require a priori knowledge of the background nor user interaction. Experimental results under realistic scenarios demonstrate the effectiveness of the method for multiple camera set ups.
本文提出了一种在有多个场景视图的情况下提取一致前景区域的方法。我们提出了一个框架，假设在每个图像中，背景和前景区域呈现不同的颜色属性，该框架可以自动识别图像中的这些区域。为了实现这一任务，单目颜色信息是不够的，我们利用空间一致性约束，即同一空间区域的多个图像投影必须满足。将单目颜色一致性约束与多视图空间约束相结合，允许我们在多视图图像中自动且同时分割前景和背景区域。与标准的背景减除方法不同，所提出的方法不需要先验的背景知识，也不需要用户交互。在现实场景下的实验结果表明了该方法对于多摄像机设置的有效性。
