ISPRS Commission III, Vol.34, Part 3A „Photogrammetric Computer Vision“, Graz, 2002
EOP and for obtaining the correspondence between the two data
sets in addition to reliably highlighting the changes.
a.
=
LAN
fe Original Points
4X Matched Points
Non-Matched Points
Figure 4. Example of detected changes between road segments
in image and object space.
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5. CONCLUSIONS AND RECOMMENDATIONS FOR
FUTURE WORK
The MIHT for robust parameter estimation technique has been
used to perform SPR for real data using free-form control linear
features without knowing the correspondence between image
and object space primitives. The proposed technique robustly
estimates the parameters. In other words, the parameters are
estimated using common features in both data sets (object and
image space features); while non-corresponding entities are
filtered out prior to the parameter estimation. An optimum
sequence for parameter estimation and the associated image
regions had been established and implemented. The proposed
method has successfully established the feature-to-feature
correspondence between the image and object space. It has also
highlighted discrepancies (changes) between the object and
image space road network and provided a quantitative measure
indicating the amount of the change. The proposed system has
the capability of integrating aerial imagery with GIS data or
terrestrial mobile mapping system for decision-making purposes
(e.g. re-mapping of road network). In this way, newly acquired
aerial imagery can undergo SPR using available control
information from a terrestrial mobile mapping system, previous
imagery, GIS database or line maps. Currently, we are analysing
the optimum pixel size of the accumulator array corresponding
to different parameters at various iterations. In addition,
generating rectified ortho-images using matched control linear
features will be investigated in future research.
Acknowledgement
The authors would like to thank Ms. Young-Ran Lee, Mr.
Hsiang Tseng Lin and Mr. Suyoung Seo for their help in
collecting the data used in the experiment section. Also, we
thank other members in the OSU photogrammetry group for the
helpful discussions and feedback.
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