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ARCHITECTURAL OBJECTS RECOGNITION TECHNIQUE IN AUGMENTED REALITY TECHNOLOGIES BASED ON CREATING A SPECIALIZED MARKERS BASE

The paper proposes a method for recognizing architectural objects when creating augmented reality mobile applications based on building a database of specialized markers. The main method of augmented reality technology for the recognition of architectural objects was chosen the technology based on special markers. The range of pattern recognition algorithms suitable for the task is highlighted. These are algorithms based on the selection of key points of images and their descriptors. The most important aim is the stable recognition of architectural objects upon mobile applications for augmented reality-type digital guide creation based on specialized markers. The scientific basis of the research is a systematic approach in the analysis of the considered markers recognition algorithms, machine learning for the development of a database of marker images and AO recognition are used. The technique consists of the following steps: processing images of architectural objects with the aim of identifying key points, obtaining descriptions of selected control points as descriptors, creating AR-metadata that correspond to architectural objects, organizing joint storage in the local database of descriptors and their corresponding metadata, visualizing the architectural object and AR metadata. To implement the stages of processing images of architectural objects and obtain descriptors of key points, algorithms for extracting key points on images, such as SIFT, MSER, SURF, RIFF, RF, are analyzed. It is shown that these algorithms are invariant to scaling, rotation, as well as resistant to changes in light, noise and viewing angle. A comprehensive use of them for processing architectural objects with the aim of obtaining descriptors of reference points was proposed. To ensure stable recognition of AO according to the developed methodology based on machine learning for processing architectural objects with the aim of obtaining descriptors of key points, it was proposed to create an additional module using an ordered stack. The launch sequence and the number of algorithms can be changed.