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Object Recognition in Digital Photogrammetry
Author(s) -
Schenk T.
Publication year - 2000
Publication title -
the photogrammetric record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 51
eISSN - 1477-9730
pISSN - 0031-868X
DOI - 10.1111/0031-868x.00149
Subject(s) - photogrammetry , computer science , cognitive neuroscience of visual object recognition , object (grammar) , artificial intelligence , multispectral image , problem statement , computer vision , 3d single object recognition , inference , strengths and weaknesses , orientation (vector space) , pattern recognition (psychology) , engineering , mathematics , philosophy , geometry , epistemology , management science
Object recognition and image understanding have increasingly become major subjects of interest for research activity in digital photogrammetry. This paper provides an overview of object recognition in photogrammetry, beginning with a problem statement and brief paradigm description. In order to exemplify the concept, automatic interior orientation is presented as an object recognition problem. Subsequent sections discuss the current status of object recognition by identifying relevant criteria, such as modelling, system strategies and inference components. Such criteria are useful for comparing object recognition systems or proposed approaches. Strengths and weaknesses of current systems are summarized, followed by a more detailed analysis of the modelling problem. Finally, two new approaches (scale‐space and fusion of multisensor/multispectral data) are mentioned. These approaches serve as examples of promising new trends which have the potential of advancing object recognition to a new level.