A Solution to the Next Best View Problem for Automated Surface Acquisition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Autonomous Active Vision System for Complete and Accurate 3D Scene Reconstruction
International Journal of Computer Vision
Learning-based robot vision: principles and applications
Learning-based robot vision: principles and applications
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This paper deals with the 3D structure estimation and exploration of a scene using active vision. Our method is based on the structure from controlled motion approach which consists in constraining the camera motion in order to obtain a precise and robust estimation of the 3D structure of a geometrical primitive. Since this approach involves to gaze on the considered primitive, we present a method for connecting up many estimations in order to recover the complete spatial structure of scenes composed of cylinders and segments. We have developed perceptual strategies able to perform a succession of robust estimations without any assumption on the number and on the localization of the different objects. Furthermore, the proposed strategy ensures the completeness of the reconstruction. An exploration process centered on current visual features and on the structure of the previously studied primitives is presented. This leads to a gaze planning strategy that mainly uses a representation of known and unknown areas as a basis for selecting viewpoints. Finally, experiments carried out on a robotic cell have proved the validity of our approach.