This award, in the Small Grants for Exploratory Research mode, will examine and test a first-principles approach for determining the relative depths of objects in images using only knowledge about the medium and the intensities acquired in a single view. Most methods for inferring depth (or range) in computer vision have depended on the use of multiple cameras and normally require the identification of corresponding points in the resulting images. Alternatively, rangefinder methods depend on sharpness-of-focus measures that require calibrated-focus lenses and an unambiguous definition of focus. The planned approach is based on the physics of light transmission and attenuation in a translucent diffuse medium. These investigators have shown, in theory and with a small set of experiments (in simulated biological tissue), that it is straightforward to infer the relative depths of structures when they are embedded in such a medium. This work is particularly exploratory because the original results arose as a byproduct of other research and so the extent of its applicability in a more general setting is not known. Two of the questions to be probed are: what are the limitations (e.g., minimum detectable depth difference) and sensitivities (to assumptions, and to changes in parameters) of the model; and what is the effect of the size and shape of the object on determination of its relative depth. The research is aimed at the development of a capability to identify unambiguously the relative depths of structures in an image, and thus to prevent confusion about which structures overlie which others. Because a single view is sufficient, it will be possible to make this identification retrospectively, as long as the properties of the medium are known. This should be useful in evaluating images arising, for example, in underwater, biological, and atmospheric applications, as well as in more-turbid environments.
