Abstract

We present a video co-segmentation method that usescategory-independent object proposals as its basic elementand can extract multiple foreground objects in a video set.The use of object elements overcomes limitations of low-level feature representations in separating complex fore-grounds and backgrounds. We formulate object-based co-segmentation as a co-selection graph in which regions withforeground-like characteristics are favored while also ac-counting for intra-video and inter-video foreground coher-ence. To handle multiple foreground objects, we expand theco-selection graph model into a proposed multi-state selection graph model (MSG) that optimizes the segmentations of different objects jointly. This extension into the MSG can be applied not only to our co-selection graph, but also can be used to turn any standard graph model into a multi-state selection solution that can be optimized directly by the existing energy minimization techniques. Our experiments show that our object-based multiple foreground videoco-segmentation method (ObMiC) compares well to related techniques on both single and multiple foreground cases.