CMRT09: Object Extraction for 3D City Models, Road Databases and Traffic Monitoring - Concepts, Algorithms, and Evaluation
can get improved, if we estimate more general geometric
primitives for representing the object’s surfaces.
Acknowledgements
This work was done within the project Ontological scales
for automated detection, efficient processing and fast visu
alisation of landscape models, which is supported by the
German Research Foundation (DFG). The authors would
also like to thank our student Frank Münster for preparing
the data and assisting the evaluation.
REFERENCES
Abraham, S. and Hau, T, 1997. Towards autonomous
high-precision calibration of digital cameras. In: SPIE,
pp. 82-93.
Binford, T, 1981. Inferring surfaces from images. Artifi
cial Intelligence 17(1-3), pp. 205-244.
Drauschke, M., 2009. An irregular pyramid for multi-scale
analysis of objects and their parts. In: GbRPR’09, LNCS
5534, pp. 293-303.
Drauschke, M., Schuster, H.-F. and Förstner, W., 2006. De
tectability of buildings in aerial images over scale space.
In: PCV’06, IAPRS 36 (3), pp. 7-12.
Fischer, B. and Buhmann, J. M., 2003. Path-based cluster
ing for grouping smooth curves and texture segmentation.
PAMI 25(4), pp. 513-518.
Fischler, M. and Bolles, R., 1981. Random sample con
sensus: A paradigm for model fitting with applications to
image analysis and automated cartography. ACM 24(6),
pp.381-395.
Förstner, W. and Gülch, E., 1987. A fast operator for de
tection and precise location of distinct points, corners and
centers of circular features. In: ISPRS Conf. on Fast Pro
cessing of Photogramm. Data, pp. 281-305.
Gallup, D., Frahm, J.-M., Mordohai, P, Yang, Q. and
Pollefeys, M., 2007. Real-time plane-sweeping stereo with
multiple sweeping directions. In: CVPR’07.
Guigues, L., Le Men, H. and Cocquerez, J.-P, 2003. The
hierarchy of the cocoons of a graph and its application to
image segmentation. Pattern Rec. Lett. 24(8), pp. 1059—
1066.
Heinrichs, M., Rodehorst, V. and Hellwich, O., 2007. Ef
ficient semi-global matching for trinocular stereo. In:
PI A’07, IAPRS 36 (3AV49A), pp. 185-190.
Heuei, S., 2004. Uncertain Projective Geometry. LNCS
3008, Springer.
Hirschmüller, H., 2005. Accurate and efficient stereo pro
cessing by semi-global matching and mutual information.
In: CVPR, pp. II: 807-814.
Hoffman, D. D. and Richards, W. A., 1984. Parts of recog
nition. Cognition 18, pp. 65-96.
Kanade, T. and Okutomi, M., 1994. A stereo matching al
gorithm with an adaptive window: Theory and experiment.
PAMI 16(9), pp. 920-932.
Khoshelham, K., 2005. Region refinement and paramet
ric reconstruction of building roofs by integration of im
age and height data. In: CMRT'05, IAPRS 36 (3AV24),
pp. 3-8.
Lâbe, T. and Fôrstner, W., 2006. Automatic relative ori
entation of images. In: Proc. 5th Turkish-German Joint
Geodetic Days.
Lowe, D., 2004. Distinctive image features from scale-
invariant keypoints. IJCV 60(2), pp. 91-110.
Martin, D., Fowlkes, C. and Malik, J., 2004. Learning
to detect natural image boundaries using local brightness,
color, and texture cues. PAMI 26(5), pp. 530-549.
Mayer, H. and Reznik, S., 2005. Building façade interpre
tation from image sequences. In: CMRT’05, IAPRS 36
(3AV24), pp. 55-60.
Pal, N. R. and Pal, S. K., 1993. A review on image seg
mentation techniques. Pattern Rec. 26(9), pp. 1277-1294.
Pan, H.-P, 1994. Two-level global optimization for image
segmentation. P&RS 49(2), pp. 21-32.
Rissanen, J., 1989. Stochastic Complexity in Statistical
Inquiry. World Scientific.
Rottensteiner, F. and Jansa, J., 2002. Automatic extraction
of buildings from lidar data and aerial images. In: CIPA,
IAPRS 34 (4), pp. 569-574.
Sahoo, P, Soltani, S. and Wong, A., 1988. A survey of
thresholding techniques. CVGIP41(2), pp. 233-260.
Schnabel, R., Wahl, R. and Klein, R., 2007. Efficient
ransac for point-cloud shape detection. Computer Graph
ics Forum 26(2), pp. 214-226.
Sohn, G., 2004. Extraction of buildings from high-
resolution satellite data and lidar. In: 20th ISPRS
Congress, IAPRS 35 (B3), pp. 1036-1042.
Tao, H. and Sawhney, H. S., 2000. Global matching cri
terion and color segmentation based stereo. In: Workshop
on Applications of Computer Vision, pp. 246-253.
Treisman, A., 1986. Features and objects in visual process
ing. Scientific American 225, pp. 114-125.
Tuytelaars, T. and Van Gool, L., 2000. Wide baseline
stereo matching based on local, affinely invariant regions.
In: BMVC, pp. 412^122.
Yang, Q., Wang, L., Yang, R., Stewénius, H. and Nistér,
D., 2009. Stereo matching with color-weighted correla
tion, hierarchical belief propagation, and occlusion han
dling. PAMI 31(3), pp. 492-504.
Zhao, J. and Lei, S., 2006. Automatic digital image en
hancement for dark pictures. In: ICASSP, pp. II: 953-956.
