Adaptive object identification and recognition using neural networks and surface signatures
The paper introduces an adaptive technique for 3D object identification and recognition in 3D scanned scenes. This technique uses neural learning of the 3D free-form surface representation of the object in study. This representation scheme captures the 3D curvature information of any free-form surface and encodes it into a 2D image corresponding to a certain point on the surface. This image represents a "surface signature" because it is unique for this point and is independent of the object translation or orientation in space.