Model-based segmentation and recognition from range data

Abstract

This paper aims at developing a model-based system for the object recognition of three-dimensional objects with curved surfaces using range images. The model data is represented using a CAD-model, providing a mathematical precise and reliable description of arbitrary shapes. The proposed method is based on model-based range image segmentation, using curvature as invariant features. By integrating model information into the segmentation stage, the segmentation process is guided to provide a partitioning corresponding to that of the CAD-model. The work provides a way to detect objects in arbitrary positions and derive the transformation onto a CAD-model. Thereby it contributes to the development of automated systems in the areas of inspection, manufacturing and robotics.