Authors:
Eckart Michaelsen
1
;
Wolfgang Middelmann
1
and
Uwe Sörgel
2
Affiliations:
1
FGAN-FOM, Germany
;
2
Institute of Photogrammetry and GeoInformation, University of Hanover, Germany
Keyword(s):
Cognitive vision, Perceptual grouping, Production systems, Blackboard control, SAR images.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Structural and Syntactic Approach
Abstract:
The laws of gestalt-perception play an important role in human vision. Psychological studies identified similarity, good continuation, proximity and symmetry as important inter-object relations that distinguish perceptive gestalts from arbitrary sets of clutter objects. Particularly, symmetry and continuation possess a high potential in detection, identification, and reconstruction of man-made objects. This contribution focuses on coding this principle in a full automatic production system. Such systems capture declarative knowledge. The procedural details are defined as control strategy for an interpreter. Often an exact solution is not feasible while approximately correct interpretations of the data with the production system are sufficient. Given input data and a given production system the control acts accumulative instead of reducing. The approach is assessment driven features any-time capability and fits well into the recently discussed paradigms of cognitive vision. An example
from the automatic extraction of groupings and symmetry in man-made structure from high resolution SAR-image data is given. The contribution also discusses the relations of such endeavour to the “mid-level” of what is today proposed as “cognitive vision”.
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