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/}
}