Model-Based Interpretation of Range Imagery

Abstract

This paper describes a model-based approach to interpreting laser range imagery. It discusses the object modeling, model-driven prediction, and feature-to-model matching aspects of the problem. The model objects are represented by a viewpoint-independent volumetric model based on generalized cylinders. Predictions of 3-D image features and their relations are generated from object models on multiple levels. These predictions give guidance for goal-directed shape extraction from low level image features. Interpretation proceeds by compar-ing the extracted image features with object models in a coarse to fine hierarchy. Since the 3-D information is available from the range image, the actual measurements are used for feature-to-model ma tch ing. A limited prototype system has been developed, preliminary results on prediction and interpretation are shown, and future research directions are discussed. I

Cite

Text

Kuan and Drazovich. "Model-Based Interpretation of Range Imagery." AAAI Conference on Artificial Intelligence, 1983.

Markdown

[Kuan and Drazovich. "Model-Based Interpretation of Range Imagery." AAAI Conference on Artificial Intelligence, 1983.](https://mlanthology.org/aaai/1983/kuan1983aaai-model/)

BibTeX

@inproceedings{kuan1983aaai-model,
  title     = {{Model-Based Interpretation of Range Imagery}},
  author    = {Kuan, Darwin T. and Drazovich, Robert J.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1983},
  pages     = {210-215},
  url       = {https://mlanthology.org/aaai/1983/kuan1983aaai-model/}
}