Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Visual Computing

ISVC 2015: Advances in Visual Computing pp 285–294Cite as

Architectural Style Classification of Building Facade Towers

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

Abstract

Architectural styles are phases of development that classify architecture in the sense of historic periods, regions and cultural influences. In the scope of an image-based architectural style classification system of building facades the current paper presents the first approach, addressing the problem of architectural style classification of facade towers. Towers are architectural structural elements symbolizing power, characteristic for ecclesiastical and secular monumental buildings, such as churches and city halls. The architectural styles classified are Romanesque, Gothic and Baroque, each spanning a few centuries and geographically widely spread in Europe. The approach is based on clustering and learning of local features. Experiments, conducted on an image database of automatically segmented towers of the observed architectural styles, achieve high classification rate.

This is a preview of subscription content, 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   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

Notes

  1. 1.

    Google Visual Search Engine http://images.google.com.

  2. 2.

    The KNN classifier parameter is noted K (upper case), not to confuse with k parameter of k-means clustering during codebook generation.

  3. 3.

    http://www.flickr.com.

References

  1. Fletcher, B.: A History of Architecture on the Comparative Method, 5th edn. Scribner’s, Batsford (1920)

    Google Scholar 

  2. Zheng, Y.T., Zhao, M., Song, Y., Adam, H., Buddemeier, U., Bissacco, A., Brucher, F., Chua, T.S., Neven, H.: Tour the world: building a web-scale landmark recognition engine. In: Proceedings of the 20th International Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Florida, USA, pp. 1085–1092. IEEE (2009)

    Google Scholar 

  3. Mathias, M., Martinovic, A., Weissenberg, J., Haegler, S., Gool, L.V.: Automatic architectural style recognition. In: Proceedings of the 4th International Workshop on 3D Virtual Reconstruction and Visualization of Complex Architectures. International Society for Photogrammetry and Remote Sensing, Trento, Italy, pp. 280–289 (2011)

    Google Scholar 

  4. Xu, Z., Tao, D., Zhang, Y., Wu, J., Tsoi, A.C.: Architectural style classification using multinomial latent logistic regression. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014, Part I. LNCS, vol. 8689, pp. 600–615. Springer, Heidelberg (2014)

    Google Scholar 

  5. Goel, A., Juneja, M., Jawahar, C.V.: Are buildings only instances?: exploration in architectural style categories. In: Proceedings of the ICVGIP 2012, Mumbai, India, pp. 1–8 (2012)

    Google Scholar 

  6. Zhang, L., Song, M., Liu, X., Sun, L., Chen, C., Bu, J.: Recognizing architecture styles by hierarchical sparse coding of blocklets. Inf. Sci. 254, 141–154 (2014)

    Article  Google Scholar 

  7. Zhang, W., Kosecka, J.: Hierarchical building recognition. Image Vis. Comput. 25(5), 704–716 (2004)

    Article  Google Scholar 

  8. Li, Y., Crandall, D., Huttenlocher, D.: Landmark classification in large-scale image collections. In: Proceedings of 12th International Conference on Computer Vision (ICCV), Kyoto, Japan, pp. 1957–1964. IEEE (2009)

    Google Scholar 

  9. Cornelis, N., Leibe, B., Cornelis, K., Gool, L.V.: 3d urban scene modeling integrating recognition and reconstruction. IJCV 78, 121–141 (2008)

    Article  Google Scholar 

  10. Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3d. ACM Trans. Graph. 25, 835–846 (2006)

    Article  Google Scholar 

  11. Illustrated architecture dictionary: Tower (2015). http://www.buffaloah.com/a/DCTNRY/t/tower.html. Accessed 4 August 2015

  12. Shalunts, G., Haxhimusa, Y., Sablatnig, R.: Architectural style classification of building facade windows. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Wang, S., Kyungnam, K., Benes, B., Moreland, K., Borst, C., DiVerdi, S., Yi-Jen, C., Ming, J. (eds.) ISVC 2011, Part II. LNCS, vol. 6939, pp. 280–289. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Collins, P.: Changing Ideals in Modern Architecture, pp. 1750–1950. McGill-Queen’s University Press, Montreal (1998)

    Google Scholar 

  14. Shalunts, G., Haxhimusa, Y., Sablatnig, R.: Classification of gothic and baroque architectural elements. In: Proceedings of the 19th IWSSIP. LNCS, Vienna, Austria, pp. 330–333. IEEE (2012)

    Google Scholar 

  15. Shalunts, G., Haxhimusa, Y., Sablatnig, R.: Architectural style classification of domes. In: Bebis, G., et al. (eds.) ISVC 2012, Part II. LNCS, vol. 7432, pp. 420–429. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  16. Shalunts, G., Haxhimusa, Y., Sablatnig, R.: Segmentation of building facade domes. In: Alvarez, L., Mejail, M., Gomez, L., Jacobo, J. (eds.) CIARP 2012. LNCS, vol. 7441, pp. 324–331. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  17. Csurka, G., Dance, C.R., Fan, L., Willamowski, J., Bray, C.: Visual categorization with bags of keypoints. In: Proceedings of International Workshop on Statistical Learning in Computer Vision, ECCV, Prague, Czech Republic, pp. 1–22 (2004)

    Google Scholar 

  18. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2), 91–110 (2004)

    Article  Google Scholar 

  19. Dudani, S.A.: The distance-weighted k-nearest neighbor rule. IEEE Trans. Syst. Man Cybern. SMC–6, 325–327 (1976)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SAIL LABS Technology GmbH, Vienna, Austria

    Gayane Shalunts

Authors
  1. Gayane Shalunts
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gayane Shalunts .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

A Appendix: The List of the Database Buildings

A Appendix: The List of the Database Buildings

The image database, gathered from the author’s own and Flickr image datasets to evaluate the performance of the tower segmentation approach, includes images of 35 cathedrals, churches, basilicas and city halls spread in Austria, Germany, Sweden, Czech Republic, Hungary, France, Spain, Luxemburg, England, Belgium, Switzerland and China. The author’s own share of the images is freely available to the scientific community here:

https://www.flickr.com/photos/lady_photographer/sets/72157636149550844/ The building names are listed below:

  1. 1.

    Vienna City Hall, Austria

  2. 2.

    Votiv church, Vienna, Austria

  3. 3.

    Maria Treu church, Vienna, Austria

  4. 4.

    Jesuit Church, Vienna, Austria

  5. 5.

    Mariahilf church, Vienna, Austria

  6. 6.

    Maria of Siege church, Vienna, Austria

  7. 7.

    Anton church, Vienna, Austria

  8. 8.

    Breitenfelder church, Vienna, Austria

  9. 9.

    Franz of Assisi church, Vienna, Austria

  10. 10.

    Altlerchenfelder church, Vienna, Austria

  11. 11.

    Salzburg Cathedral, Austria

  12. 12.

    Cologne Cathedral, Germany

  13. 13.

    St. Pantaleon Church, Cologne, Germany

  14. 14.

    Bremen Cathedral, Germany

  15. 15.

    Fulda Cathedral, Germany

  16. 16.

    Basilica St. Castor, Koblenz, Germany

  17. 17.

    St. Gall Abbey, Switzerland

  18. 18.

    Notre Dame Cathedral, Paris, France

  19. 19.

    Reims Cathedral, France

  20. 20.

    Abbaye Aux Hommes Caen, France

  21. 21.

    York Minster, England

  22. 22.

    Westminster Abbey, London, England

  23. 23.

    Barcelona Cathedral, Spain

  24. 24.

    Burgos Cathedral, Spain

  25. 25.

    St. Michael and St. Gudula Cathedral, Brussels, Belgium

  26. 26.

    Brussels City Hall, Belgium

  27. 27.

    Church of Our Lady of Laeken, Brussels, Belgium

  28. 28.

    St. Petrus And St. Paulus Church, Ostend, Belgium

  29. 29.

    Loreta church, Prague, Czech Republic

  30. 30.

    St.Peter and St.Paul Church Vysehrad, Prague, Czech Republic

  31. 31.

    St. Mary Magdalene church, Karlovy Vary, Czech Republic

  32. 32.

    St. Stefan’s Cathedral, Budapest, Hungary

  33. 33.

    Church Saints Cosmas and Damian, Luxemburg

  34. 34.

    Lund Cathedral, Sweden

  35. 35.

    St. Michael’s Cathedral, Qingdao, China

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Shalunts, G. (2015). Architectural Style Classification of Building Facade Towers. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27857-5_26

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation