E. González, A. Adán, V. Feliú, and L. Sánchez (Spain)
3D recognition, next best view, active recognition system
This paper describes a new strategy of optimal view point selection for 3D object recognition purposes. Feature vectors of an object viewed from specific viewpoints are mapped on the nodes of a tessellated sphere which we call D-Sphere. The next best view (NBV) is established on the D-Sphere and is defined as the view that yields the maximum dissimilarity among the set of candidate objects (hypotheses). The purpose of finding a NBV is discriminating quickly between hypotheses. Our method aligns all hypotheses into a tessellated sphere. Then it calculates the view point (node) which exhibits the maximum dissimilarity among the corresponding views of the candidate objects. The node values of the D-Sphere are weighted taking into account the kinematics costs involved in the movement of the robot arm that carries the camera. Experiments with a robotic hand-eye system are also described
Important Links:
Go Back
