Model-based segmentation and recognition from range data.
Presented at: UNSPECIFIED.
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.
|Type:||Conference item (UNSPECIFIED)|
|Title:||Model-based segmentation and recognition from range data|
|Keywords:||CAD, Object recognition, Range image, Segmentation|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Civil, Environmental and Geomatic Engineering
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