LandScan: A Natural Language and Computer Vision System for Analyzing Aerial Images
Proceedings of the Ninth International Joint Conference on Artificial Intelligence. Perception. Pages 919-920.
Abstract
LandScan (LANguage Driven SCene ANalysis) is presented as an integrated vision system which covers most Ievels of both VISIOn and natural language processing. Computations are both data-driven and query-driven . In the report we focus on the design of the vision and control modules. Future work will investigate in more detail the design of the natural language interface. The data-driven system employs active control of stereo camcras for image acquisition, and dynamically constructs a surface model from multiple aerial views of an urban scene. The query-driven system allows the user's natural l:m guage queries to focus analysis to pertincnt regions of the scene. This is different than many image understanding systems which present a symbolic description of the entire scene regardless of what portions of that picture are actually of interest.
@inproceedings{ijcai1985p185,
title = {LandScan: A Natural Language and Computer Vision System for Analyzing Aerial Images},
author = {Bajcsy, Ruzena and Joshi, Aravind K. and Krotkov, Eric and Zwarico, Amy E.},
booktitle = {Proceedings of the Ninth International Joint Conference on
Artificial Intelligence, {IJCAI-85}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Aravind Joshi},
pages = {919--920},
year = {1985},
note = {Perception},
url = {https://ijcai.org/proceedings/1985/185},
}
TY - CPAPER TI - LandScan: A Natural Language and Computer Vision System for Analyzing Aerial Images AU - Bajcsy, Ruzena AU - Joshi, Aravind K. AU - Krotkov, Eric AU - Zwarico, Amy E. T2 - Proceedings of the Ninth International Joint Conference on Artificial Intelligence, IJCAI-85 PB - International Joint Conferences on Artificial Intelligence PY - 1985 SP - 919 EP - 920 UR - https://ijcai.org/proceedings/1985/185 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: