3-D Object recognition from point clouds

The future market for real-time 3-D mapping extends far beyond traditional geospatial applications and includes the navigation of an unmanned autonomous vehicle (UAV). Extensive parallel processes such as graphics processing unit (GPU) computing make real-time 3-D object recognition and mapping achievable. Geospatial technology such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house. Automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because the radiometric properties of an object vary considerably from image to image. Geospatial information technology such as digital photogrammetry provides location. We believe the next breakthrough may be automatically identifying 3-D objects. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization applications, it has the potential to be valuable in robotics and UAV applications.