Embedded Shape Matching in Photogrammetry Data for Modeling Making
  Knowledge
Demircan Tas Mine Özkar
In three-dimensional models obtained by photogrammetry of existing
structures, all of the shapes that the eye can select cannot always find their
equivalents in the geometric components of the model. However, the matching of
meaningful parts and assemblages with the records acquired with rapid and
detailed documentation methods will provide an advantage for the creation of
information models of existing structures. While aiming to produce answers to
this problem and in order to overcome the difficulties of pattern recognition
in three-dimensional models, we used two-dimensional samples obtained by
projection. Processing techniques such as ambient occlusion, curvature and
normal maps are commonly used in modern computer graphics applications that
enable the representation of three-dimensional surface properties in
two-dimensional data sets. The method we propose is based on the recognition of
patterns through these mappings instead of the usual light-based visualization.
The first stage of the application is photogrammetric capture of a few examples
of Zeugma mosaics and three-dimensional digital modeling of a set of Seljuk era
brick walls based on knowledge obtained through architectural history
literature. The second stage covers the creation of digital models byprocessing
the surface representation obtained from this data using Alice Vision,
OpenCV-Python, and Autodesk Maya to include information on aspects of the
making of the walls. What is envisioned for the next stages is that the mapping
data contributes and supports the knowledge for rule-based design and making
processesof cultural heritage.