Matching Aerial Images to 3-D Terrain Maps

Jeffrey J. Rodríguez; J. K. Aggarwal

doi:10.1109/34.62603

Matching Aerial Images to 3-D Terrain Maps

Jeffrey J. Rodríguez, J. K. Aggarwal

Research output: Contribution to journal › Article › peer-review

78 Scopus citations

Abstract

A new terrain matching algorithm is presented for use in a passive aircraft navigation system. A sequence of aerial images is matched to a reference digital map of the 3-D terrain. Stereo analysis of successive images results in a recovered elevation map. A “cliff map” is then used as a novel compact representation of the 3-D surfaces. The position and heading of the aircraft are determined via a terrain matching algorithm that locates the unknown cliff map within the reference cliff map. The robustness of the matching algorithm is demonstrated by experimental results using real terrain data.

Original language	English (US)
Pages (from-to)	1138-1149
Number of pages	12
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	12
Issue number	12
DOIs	https://doi.org/10.1109/34.62603
State	Published - Dec 1990

Keywords

Aircraft navigation
digital elevation maps
image sequence analysis
shape matching
stereo
terrain matching

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/34.62603

Cite this

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title = "Matching Aerial Images to 3-D Terrain Maps",

abstract = "A new terrain matching algorithm is presented for use in a passive aircraft navigation system. A sequence of aerial images is matched to a reference digital map of the 3-D terrain. Stereo analysis of successive images results in a recovered elevation map. A “cliff map” is then used as a novel compact representation of the 3-D surfaces. The position and heading of the aircraft are determined via a terrain matching algorithm that locates the unknown cliff map within the reference cliff map. The robustness of the matching algorithm is demonstrated by experimental results using real terrain data.",

keywords = "Aircraft navigation, digital elevation maps, image sequence analysis, shape matching, stereo, terrain matching",

author = "Rodr{\'i}guez, {Jeffrey J.} and Aggarwal, {J. K.}",

note = "Funding Information: Dr. Rodriguez is a member of Eta Kappa Nu, Tau Beta Pi, Sigma and Phi Kappa Phi. During his graduate work, he was the recipient of a National Science Foundation Graduate Fellowship and a G.E.M./IBM Graduate Fellowship. Funding Information: Manuscript received June 14, 1989; revised March 7, 1990. Recommended for acceptance by J.L. Mundy. This work was supported by the Army Research Office under Contract DN3-87-K-0089. J. J. Rodriguez was with the Computer and Vision Research Center, University of Texas at Austin, Austin, TX 78712. He is now with the Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721. J. K. Agganval is with the Computer and Vision Research Center, University of Texas at Austin, Austin, {\textquoteleft}IX 78712. IEEE Log Number 9038391.",

year = "1990",

month = dec,

doi = "10.1109/34.62603",

language = "English (US)",

volume = "12",

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AU - Rodríguez, Jeffrey J.

AU - Aggarwal, J. K.

N1 - Funding Information: Dr. Rodriguez is a member of Eta Kappa Nu, Tau Beta Pi, Sigma and Phi Kappa Phi. During his graduate work, he was the recipient of a National Science Foundation Graduate Fellowship and a G.E.M./IBM Graduate Fellowship. Funding Information: Manuscript received June 14, 1989; revised March 7, 1990. Recommended for acceptance by J.L. Mundy. This work was supported by the Army Research Office under Contract DN3-87-K-0089. J. J. Rodriguez was with the Computer and Vision Research Center, University of Texas at Austin, Austin, TX 78712. He is now with the Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721. J. K. Agganval is with the Computer and Vision Research Center, University of Texas at Austin, Austin, ‘IX 78712. IEEE Log Number 9038391.

PY - 1990/12

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N2 - A new terrain matching algorithm is presented for use in a passive aircraft navigation system. A sequence of aerial images is matched to a reference digital map of the 3-D terrain. Stereo analysis of successive images results in a recovered elevation map. A “cliff map” is then used as a novel compact representation of the 3-D surfaces. The position and heading of the aircraft are determined via a terrain matching algorithm that locates the unknown cliff map within the reference cliff map. The robustness of the matching algorithm is demonstrated by experimental results using real terrain data.

AB - A new terrain matching algorithm is presented for use in a passive aircraft navigation system. A sequence of aerial images is matched to a reference digital map of the 3-D terrain. Stereo analysis of successive images results in a recovered elevation map. A “cliff map” is then used as a novel compact representation of the 3-D surfaces. The position and heading of the aircraft are determined via a terrain matching algorithm that locates the unknown cliff map within the reference cliff map. The robustness of the matching algorithm is demonstrated by experimental results using real terrain data.

KW - Aircraft navigation

KW - digital elevation maps

KW - image sequence analysis

KW - shape matching

KW - stereo

KW - terrain matching

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Matching Aerial Images to 3-D Terrain Maps

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