Reasoning about 3D scene structure is an important component of visual scene understanding. Often, reasoning proceeds from low-level cues without resorting to full 3D reconstruction. However, existing geometric cues may require multiple viewpoints, supervised training, constraints on scene structure or information from auxiliary sensors. To address these limitations, this paper demonstrates how geometric context for a single static camera can be recovered from the location and shape of moving foreground targets. In particular, we propose methods to compute the likelihood of a static occlusion boundary and floor region at each pixel. Importantly, these cues do not require supervised training, or prior knowledge of camera geometry or scene structure. Finally, we show how the proposed geometric cues can be used to infer an ordinal depth map and demonstrate its use in compositing with correct occlusion handling.
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