The most remarkable aspects of Sight Power data mining technology are the set of effective techniques and algorithms for spatial data effective indexing and compression, spatial object recognition and spatial scene reconstruction. The developed algorithms transform visual data into the CAD-like models (set of 3D-objects). These models allow dealing with each object as a unique geometric entity. The models can be used for example, to measure distance and angles between objects, or for the calculation of object volume.
The methods used by Sight Power for aforementioned algorithms are very versatile, but in most cases they are based on a combination of fuzzy logic and geometrical and statistical analysis.
The input information used for object recognition is most often either scanned point data (“point cloud”), or images, or a combination of both.
Methods and algorithms developed by the Sight Power team are scalable and they can be effectively used for real-time application.
Sight Power data mining technology in the nutshell means:
- converting spatial info into the effective business solutions;
- using spatial analysis for everyday production operations;
- extracting significance from expanses of noisy spatial data;
- getting value from smart combination of old and innovative spatial data sources;
- integrating collection and processing of spatial data.