Occlusion cues for image scene layering

1077-3142/$ see front matter 2012 Elsevier Inc. A http://dx.doi.org/10.1016/j.cviu.2012.10.001 q This paper has been recommended for acceptance ⇑ Corresponding author. E-mail address: [email protected] (Q. Li). To bring computer vision closer to human vision, we attempt to enable computer to understand the occlusion relationship in an image. In this paper, we propose five low dimensional region-based occlusion cues inspired by the human perception of occlusion. These cues are semantic cue, position cue, compactness cue, shared boundary cue and junction cue. We apply these cues to predict the region-wise occlusion relationship in an image and infer the layer sequence of the image scene. A preference function, trained with samples consisting of these cues, is defined to predict the occlusion relationship in an image. Then we put all the occlusion predictions into the layering algorithm to infer the layer sequence of the image scene. The experiments on rural, artificial and outdoor scene datasets show the effectiveness of our method for occlusion relationship prediction and image scene layering. 2012 Elsevier Inc. All rights reserved.