Informatica

The innovations and improvements in digital imaging sensors and scanners, computer modeling, haptic equipments and e-learning technology, as well as the availability of many powerful graphics PCs and workstations make haptic-based rendering methods for e-learning documentation with 3-D modeling functionality feasible. E-Learning documentation is a new term in computing, engineering and architecture, related to digital documentation with e-learning functionality, and introduced to literature for the first time within this paper. In particular, for the historical living systems (architectures, monuments, cultural heritage sites), such a methodolgy must be able to derive pictorial, geometric, spatial, topological, learning and semantic information from the target architectural object (historical living system), in such a way that it can be directly used for e-learning purposes regarding the history, the architecture, the structure and the temporal (time-based) 3-D geometry of the projected historical living system. A practical project is used to demonstrate the functionality and the performance of the proposed methodology. In particular, the processing steps from image acquisition to e-learning documentation of the Aghios Achilleios basilica, twin lakes Prespes, Northern Greece, through its 3-D geometric CAAD (Computer-Aided Architectural Design) model and semantic description are presented. Also, emphasis is placed on introducing and documenting the new term e-learning documentation. Finaly, for learning purposes related to 3-D modeling accuracy evaluation, a comparison test of two image-based approaches is carried out and discussed.

The study of 3‐D indoor accurate scenery modeling is an active research area. The produced model can be used in a number of virtual reality applications, in digital documentation of monuments and sites, and so on. Digital photogrammetry and CAD technology have to play a vital role in this field. Photogrammetry's contribution is mainly on data acquisition from imagery, whilst the necessary image knowledge is derived from geometry and topology of image contents. While the first is traditionally used, the second one only lately is been tackled.