The results from the evaluation suggest that the approach taken can serve to refine existing task characterizations to reflect the cognitive visual operations that spatial data and geovisualizations can support.
Thereby, we provide a reliable 3D representation of the shapes in the scene that can then be used for higher level visual operations, where contextual knowledge may be available.
That this can happen is a well-known empirical fact but that it can originate in basic automatic visual operations that precede conscious representation is surprising and in some sense worrying as it seems to work against the scientific ideal that careful observation is sufficient to reach agreements about basic facts and what we consider reality.
Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations.
This theory can also be used for raising questions about which animals have early receptive fields with properties compatible with general purpose visual operations according to the notion of an idealized visual front end.
Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation.
Hence, these receptive field profiles can generally serve as a basis for expressing a large number of visual operations and have empirically been shown to lead to robust algorithms.
In this paper, we outline an approach that defines visualizations operations or basic visual actions that implement a viewer's task of exploration and characterization of geospatial structures in data or phenomena.
Construction workers with daily access to visual plant operation were able to easily identify potential safety problems.
