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An agent-based paradigm for the reconstruction of conical perspectives
Ist Teil von
Expert systems with applications, 2016-08, Vol.55, p.1-20
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2016
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
•A system that allows obtaining three-dimensional models from two-dimensional entities is proposed.•The use of an agent-based architecture enables the scalability of the platform.•The paradigm has been implemented and simulated, obtaining a success ratio of 100%.
Obtaining three-dimensional models from digital images is one of the most important challenges in the computer vision. This task requires the advances in two major investigation fields: on the one hand the vectorization of the digital image to turn bitmaps into a set of geometrical entities (graph), on the other hand the reconstruction of the three-dimensional model from these two-dimensional entities. This work is focused on the second task, that is, the reconstruction of a three-dimensional model from a graph.
We have focused on the reconstruction of graphs with parallel and oblique perspectives with two vanishing points, and we propose an algorithm in order to identify this typology in contrast to the proposals kwon so far, in which it is assumed that the graph always represents an oblique perspective with three vanishing points from which greater information of the three-dimensional model can be extracted.
On the other hand, the current reconstruction algorithms require a previous knowledge of the faces defined in the model which must be obtained from the starting graph, task that is not currently solved completely, generates many erroneous results, requires interacting with the user and involves a high computing cost.
The reconstruction algorithms proposed in this work do not require the knowledge of the faces of the model, it is completely automatic and we have obtained a success rate of 100% in the graphs with normalon and quasi-normalon typology tested.
Regarding to practical advantages and research contribution in expert and intelligent systems, we propose, for the first time, an architecture based on agents for the reconstruction which allows, on the one hand, the simultaneous reconstruction of graphs considerably reducing the computing cost and, on the other hand, adding, with less effort, new reconstruction techniques to deal with graphs with other typologies.