Automatic depth profiling of 2D cinema - and photographic images

It is generally understood that interpreting depth from monoscopic images inherently induces the problem of object segmentation and context recognition. A common way to deal with this complexity is to focus on one aspect (e.g. segmentation) and largely constrain or skip the other (e.g. scene classification). In our approach, we practically reconcile the two paths. We start by defining several depth profiles, providing rough estimates for both background and foreground, while reflecting common photographic and cinematic practices and rules. The idea is to assign one or more of these profiles to an image - based on the output of multiple classifiers, and apply an image-adaptive bilateral filter to align the depth with object edges. From extensive trials, we conclude that robust classification and visual performance can be achieved with this approach on a variety of content.