Volume: 12, Issue: 1(2003)
pp. 57-79 DOI: 10.1142/S0218213003001113
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Abstract |
Full Text (PDF, 2,705KB)
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References
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| Title: |
KNOWLEDGE SUPERVISED PERCEPTUAL GROUPING BASED
QUALITATIVE BUILDING DETECTION FROM MONOCULAR AERIAL IMAGES |
| Author(s): |
ZHONGFEI (MARK) ZHANG
Computer Science Department,
Watson School of Engineering and Applied Science,
State University of New York at Binghamton,
Binghamton, NY 13902 - 6000, USAROHINI K. SRIHARI
Center of Excellence for Document
Analysis and Recognition, State University of New York at Buffalo,
Buffalo, NY 14228 - 2567, USA
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| History: |
Received 17 April 2002
Accepted 7 January 2003
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| Abstract: |
This paper addresses an important and practical problem in computer
vision and pattern recognition — qualitative target detection from
aerial images. In particular, it discusses the problem of qualitative
building detection based on a monocular aerial image. The approach
proposed, due to its independence of site models or camera calibration
information, complements the model based approaches developed in the
rest of the research community of building detection from aerial
images. Specifically, a knowledge supervised perceptual grouping (KSPG)
system based on reinvestigation, and hypothesis generation and verification, is
presented, and is shown to be reasonably robust in experiments using real data. |
| Keywords: |
Qualitative building detection; knowledge supervised perceptual grouping; reinvestigation; hypothesis generation and verification; distance map; dynamic matching
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