Skip to main content
SpringerLink
Log in

Regionwise Classification of Building Facade Images

  • Conference paper
Photogrammetric Image Analysis (PIA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6952))

Included in the following conference series:

Abstract

In recent years, the classification task of building facade images receives a great deal of attention in the photogrammetry community. In this paper, we present an approach for regionwise classification using an efficient randomized decision forest classifier and local features. A conditional random field is then introduced to enforce spatial consistency between neighboring regions. Experimental results are provided to illustrate the performance of the proposed methods using image from eTRIMS database, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Barnard, K., Duygulu, P., Freitas, N.D., Forsyth, D., Blei, D., Jordan, M.: Matching words and pictures. Journal of Machine Learning Research 3, 1107–1135 (2003)

    MATH  Google Scholar 

  • Bosch, A., Zisserman, A., Muñoz, X.: Image classification using random forests and ferns. In: IEEE International Conference on Computer Vision, pp. 1–8 (2007)

    Google Scholar 

  • Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 1124–1137 (2004)

    Article  MATH  Google Scholar 

  • Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 1222–1239 (2001)

    Article  Google Scholar 

  • Breiman, L.: Random forests. Machine Learning 45(1), 5–32 (2001)

    Article  MATH  Google Scholar 

  • Comaniciu, D., Meer, P.: Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5), 603–619 (2002)

    Article  Google Scholar 

  • Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 886–893 (2005)

    Google Scholar 

  • Drauschke, M., Förstner, W.: Selecting appropriate features for detecting buildings and building parts. In: Proceeding of the 21st Congress of the International Society for Photogrammetry and Remote Sensing (ISPRS), vol. (B3b), pp. 447–452 (2008)

    Google Scholar 

  • Drauschke, M., Mayer, H.: Evaluation of texture energies for classification of facade images. In: ISPRS Technical Commission III Symposium on Photogrammetry Computer Vision and Image Analysis, pp. 257–262 (2010)

    Google Scholar 

  • Dumont, M., MarĂ©e, R., Wehenkel, L., Geurts, P.: Fast multi-class image annotation with random subwindows and multiple output randomized trees. In: International Conference on Computer Vision Theory and Applications (VISAPP), vol. 2, pp. 196–203 (2009)

    Google Scholar 

  • Fröhlich, B., Rodner, E., Denzler, J.: A fast approach for pixelwise labeling of facade images. In: International Conference on Pattern Recognition, pp. 3029–3032 (2010)

    Google Scholar 

  • Geurts, P., Ernst, D., Wehenkel, L.: Extremely randomized trees. Machine Learning 63(1), 3–42 (2006)

    Article  MATH  Google Scholar 

  • Gould, S., Rodgers, J., Cohen, D., Elidan, G., Koller, D.: Multi-class segmentation with relative location prior. International Journal of Computer Vision 80(3), 300–316 (2008)

    Article  Google Scholar 

  • Kluckner, S., Bischof, H.: Image-based building classification and 3d modeling with super-pixels. In: ISPRS Technical Commission III Symposium on Photogrammetry Computer Vision and Image Analysis, pp. 233–238 (2010)

    Google Scholar 

  • Kolmogorov, V., Zabih, R.: What energy functions can be minimized via graph cuts? IEEE Transactions on Pattern Analysis and Machine Intelligence 26(2), 147–159 (2004)

    Article  MATH  Google Scholar 

  • KorÄŤ, F., Förstner, W.: Interpreting terrestrial images of urban scenes using discriminative random fields. In: Proceeding of the 21st Congress of the International Society for Photogrammetry and Remote Sensing (ISPRS), pp. 291–296 (2008)

    Google Scholar 

  • KorÄŤ, F., Förstner, W.: eTRIMS image database for interpreting images of man-made scenes. Technical Report TR-IGG-P-2009-01 (2009), http://www.ipb.uni-bonn.de/projects/etrims_db

  • Kumar, S., Hebert, M.: Discriminative random fields: a discriminative framework for contextual interaction in classification. In: IEEE International Conference on Computer Vision, pp. 1150–1157 (2003)

    Google Scholar 

  • Lafferty, J., McCallum, A., Pereira, F.: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: International Conference on Machine Learning, pp. 282–289 (2001)

    Google Scholar 

  • Lazaridis, G., Petrou, M.: Image registration using the Walsh transform. IEEE Transactions on Image Processing 15(8), 2343–2357 (2006)

    Article  Google Scholar 

  • Lepetit, V., Lagger, P., Fua, P.: Randomized trees for real-time keypoint recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 775–781 (2005)

    Google Scholar 

  • Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

  • Maree, R., Geurts, P., Piater, J., Wehenkel, L.: Random subwindows for robust image classification. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 34–40 (2005)

    Google Scholar 

  • Petrou, M., Bosdogianni, P.: Image Processing: The Fundamentals. Wiley, Chichester (1999)

    Book  Google Scholar 

  • Ripperda, N., Brenner, C.: Evaluation of structure recognition using labelled facade images. In: Denzler, J., Notni, G., SĂĽĂźe, H. (eds.) Pattern Recognition. LNCS, vol. 5748, pp. 532–541. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  • Rottensteiner, F., Trinder, J., Clode, S., Kubik, K.: Building detection by fusion of airborne laser scanner data and multi-spectral images: Performance evaluation and sensitivity analysis. ISPRS Journal of Photogrammetry and Remote Sensing 62(2), 135–149 (2007)

    Article  Google Scholar 

  • Schnitzspan, P., Fritz, M., Schiele, B.: Hierarchical support vector random fields: joint training to combine local and global features. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 527–540. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  • Shotton, J., Johnson, M., Cipolla, R.: Semantic texton forests for image categorization and segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)

    Google Scholar 

  • Shotton, J., Winnand, J., Rother, C., Criminisi, A.: Textonboost: joint appearance, shape and context modeling for multi-class object recognition and segmentation. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 1–15. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  • Sivic, J., Russell, B.C., Efros, A.A., Zisserman, A., Freeman, W.T.: Discovering objects and their locations in images. In: IEEE International Conference on Computer Vision, pp. 1–8 (2005)

    Google Scholar 

  • Teboul, O., Simon, L., Koutsourakis, P., Paragios, N.: Segmentation of building facades using procedural shape priors. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3105–3112 (2010)

    Google Scholar 

  • Vedaldi, A., Fulkerson, B.: Vlfeat: An open and portable library of computer vision algorithms (2008), http://www.vlfeat.org/

  • Verbeek, J., Triggs, B.: Region classification with markov field aspect models. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)

    Google Scholar 

  • Wenzel, S., Förstner, W.: Semi-supervised incremental learning of hierarchical appearance models. In: Proceeding of the 21st Congress of the International Society for Photogrammetry and Remote Sensing (ISPRS), vol. (B3b), pp. 399–405 (2008)

    Google Scholar 

  • Yang, M.Y., Förstner, W., Drauschke, M.: Hierarchical conditional random field for multi-class image classification. In: Proceedings of the Fifth International Conference on Computer Vision Theory and Applications, vol. 2, pp. 464–469 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Photogrammetry, Institute of Geodesy and Geoinformation, University of Bonn, Nussallee 15, 53115, Bonn, Germany

    Michael Ying Yang & Wolfgang Förstner

Authors
  1. Michael Ying Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wolfgang Förstner
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Photogrammetry and Remote Sensing, Technische Universität München, Arcisstr. 21, 80333, München, Germany

    Uwe Stilla

  2. Institute of Photogrammetry and Geoinformation, Leibniz Universität, Hannover Nienburger Str. 1, 30167, Hannover, Germany

    Franz Rottensteiner

  3. Chair for Photogrammetry and Remote Sensing, Universität der Bundeswehr, Werner-Heisenberg-Weg 39, 85577, München, Neubiberg, Germany

    Helmut Mayer

  4. Institute of Photogrammetry& Remote Sensing, Karlsruhe Institute of Technology, Englerstr. 7, 76131, Karlsruhe, Germany

    Boris Jutzi

  5. Remote Sensing Technology, Technische Universität München, Arcisstr. 21, 80333, München, Germany

    Matthias Butenuth

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yang, M.Y., Förstner, W. (2011). Regionwise Classification of Building Facade Images. In: Stilla, U., Rottensteiner, F., Mayer, H., Jutzi, B., Butenuth, M. (eds) Photogrammetric Image Analysis. PIA 2011. Lecture Notes in Computer Science, vol 6952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24393-6_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24393-6_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24392-9

  • Online ISBN: 978-3-642-24393-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation