International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
4. CONCLUSSION
The paper has presented the fully automatic framework for
efficient reconstruction of building outlines from LIDAR data
based on their geocoded address information. The presented
results were obtained without any manual refinement. In the
first step, separated buildings regions were easily marked in the
interpolated high image based on their initial location from the
address points. Then, the pixels detected as a boundary were
projected onto the original data in order to deliver the set of
boundary points contaminated by outliers. The data set serves as
the input for RANSAC algorithm, which detects straight lines
and delivers initial boundary. Finally, the boundaries were
subjected to the regularization according to parallelism and
rectangularity constraints that usually characterize a building.
The presented approach was applied to the dense residential
area with complex building shapes. The work presented in this
paper is still in progress and improvement in regularization
approach would significantly increase the whole algorithm
performance.
The idea to utilize building address points for building outlines
reconstruction is new and it has shown good potential. The
number of web portals that freely share geocoded information
increases rapidly together with a development of information
society. Although the data — collected in different ways - cannot
be treated as completely reliable information, it might be
sufficient to serve as the initial hint for further computation and
analyses. Moreover, it gives an opportunity to easily connect
reconstructed buildings with all the information available in
open databases. The work presented in that paper was focused
on the methodology of building reconstruction using initial
information about their location. In the further work real open
source information will be utilized. The quantitative accuracy
analysis indicates that 9096 of buildings were detected well in
comparison to the reference cadastral data.
KAPITAL LUDZKI ; DOLNY ia APRA
NARODOWA STRATEGIA SFÔINOSC s EU SLASK FUNDUSZ SPOLECZNY
The task is co-financed by the European Union under the
European Social Fund.
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