The Monocular Automated Building System (MABS)

Our work is based on USC-MABS: it requires only one image with tilt angle, swing angle and sun direction as input and assumes weak perspective. The building model which is used here consists of rectangular parallelepipeds that can be composed to, for example, L,T or I-shapes. After a linear feature extraction roof-hypotheses are formed by an hierarchical perceptual grouping (lines, folded lines, parallels, U-contours, parallelograms). This step creates a large number of parallelograms, allowing the establishment of also weak hypotheses. Next the parallelograms are selected by local and global criteria using domain knowledge and shadow- and wall information. Finally a verification is applied to validate the selected hypotheses using shadow and wall evidence. This step results in a three-dimensional model of the building, which is determined by the associated shadow and wall evidence.

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The system performs reliably on images where the buildings are separated, wall-, shadow- or roof-lines are at least partially well detected. Otherwise, it may fail to derive a three-dimensional description of a building, even if there is information extracted that at least partly contain the desired result. A rejection of a correct hypothesis can occur during verification or during selection. A correction here would just be to specify this particular parallelogram. It is also possible that the correct hypothesis is not generated due to lack of existing features in the image. Still partly correct hypotheses are likely to exist and the missing feature(s) have to be added to obtain a correct description of a building.