Resolution Il.6 Integration of information into GIS
The Congress
Noting
the increasing need for up-to-date geospatial informa-
tion and the lack of efficient, timely revision of such
information in many areas
Recognising
that multispectral and stereoscopic imagery can provide
such information and is becoming increasingly impor-
tant for use in geographic information systems (GIS)
Recommends
that the integration of photogrammetric and remote
sensing imagery and techniques into GIS for efficient
acquisition and revision of geospatial information be
strengthened.
Resolution 11.7 End-to-end systems
The Congress
Noting
the much increased use of geospatial information in all
areas of public and commercial activity
Recognising
the need for efficient processing and presentation of
such data in a value-added form
Recommends
the development and validation of end-to-end pro-
cessing systems for specific applications, making use
of a range of imaging systems, a range of components
from the spatial information sciences and paying par-
ticular attention to techniques for the delivery and pres-
entation of information.
Resolutions of Technical Commission III
Resolution IIl.1 Surface reconstruction
The Congress
Noting
the extensive use of automated surface reconstruction
for mapping, image rectification and 3D modelling
the emergence of laser scanning technology as an
additional information source about surfaces
the role of surface reconstruction in the general frame-
work of object recognition and scene analysis
Recognising
the need for further theoretical investigations into the
automatic reconstruction of surfaces, including their
segmentation, and of conducting reliability studies
Recommends
that research be continued on Earth surface reconstruc-
tion techniques with emphasis on multiple sensor input.
Resolution III.2 Fusion
The Congress
Noting
the increasing availability of new sensors and the use
of multi-sensor, multi-resolution systems
Recognising
the need for extending theories and developing algo-
rithms for merging multi-sensor data
modelling of uncertainty in multi-sensor fusion
incorporating GIS information to support object recog-
nition
evaluating the efficiency and performance of multi-sen-
sor fusion
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Recommends
- that fusion, at the data, feature and information levels,
be promoted.
Resolution Ill.3 Object modelling
The Congress
Noting
- the importance of modelling 3D objects related to
object recognition and image understanding
Recognising
- that further progress in the automatic recognition of
objects relies on improved models
Recommends
- that efforts be strengthened in developing generic
models of objects, including their geometric, semantic
and temporal properties, and interrelationships.
Resolution IIl.4 Combining classification methods and
computer vision
The Congress
Noting
- the increased availability of multi-sensor, multi-spectral
and hyper-spectral data
Recognising
- the need for combining traditional classification methods
of remote sensing with computer vision approaches for the
automatic recognition of objects
Recommends
- that efforts be strengthened in combining classification
methodologies and computer vision approaches into a
common object recognition framework.
Resolution 111.5 Performance and reliability of
algorithms
The Congress
Noting
- the diversity of algorithms in photogrammetry, remote
sensing and computer vision developed for the pur-
pose of feature extraction and object recognition
Recognising
- the need for assessing the performance, reliability and
availability of algorithms
Recommends
- that procedures for evaluating algorithms and for
developing suitable test datasets be intensified and
formulated.
Resolution 111.6 Image understanding / object
recognition
The Congress
Noting
- the importance of theoretical and conceptual investi-
gations in object recognition and image understanding
Recognising
- that despite major efforts and good progress achieved
from 1996 to 2000 there remain considerable gaps in
the theory for automation of feature extraction and
recognition
Recommends
- that investigations in object recognition and image
understanding be intensified, particularly in the areas
of modelling and knowledge engineering
- that co-operation with researchers in computer vision
and cognitive science also be intensified.
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