A next-best-view system for autonomous 3-D object reconstruction

The focus of this paper is to design and implement a system capable of automatically reconstructing a prototype three-dimensional (3-D) model from a minimum number of range images of an object. Given an ideal 3-D object model, the system iteratively renders range and intensity images of the model from a specified position, assimilates the range information into a prototype model, and determines the sensor pose (position and orientation) from which an optimal amount of previously unrecorded information may be acquired. Reconstruction is terminated when the model meets a given threshold of accuracy. Such a system has applications in the context of robot navigation, manufacturing, or hazardous materials handling. The system has been tested successfully on several synthetic data models, and each set of results was found to be reasonably consistent with an intuitive human search. The number of views necessary to reconstruct an adequate 3-D prototype depends on the complexity of the object or scene and the initial data collected. The prototype models which the system recovers compare well with the ideal models.