Relative Position Descriptors - A Review

Mohammad Naeem, Pascal Matsakis

2015

Abstract

A relative position descriptor is a quantitative representation of the relative position of two spatial objects. It is a low-level image descriptor, like colour, texture, and shape descriptors. A good amount of work has been carried out on relative position description. Application areas include content-based image retrieval, remote sensing, medical imaging, robot navigation, and geographic information systems. This paper reviews the existing work. It identifies the approaches that have been used as well as the properties that can be expected from relative position descriptors. It compares and provides a brief overview of various descriptors, including their main properties, strengths and limitations, and it suggests areas for future work.

References

  1. J. F. Allen, 1983. “Maintaining Knowledge About Temporal Intervals,” Communications of the ACM, 26(11): 832-43.
  2. I. Bloch, 2005. “Fuzzy Spatial Relationships for Image Processing and Interpretation: A Review,” Image and Vision Computing, 23(2):89-110.
  3. A. Buck, J. Keller, M. Skubic, 2013. “A Memetic Algorithm for Matching Spatial Configurations with the Histograms of Forces,” IEEE Trans. on Evolutionary Computation, 17(4):588-604.
  4. A. G. Cohn, B. Bennett, J. Gooday, N. M. Gotts, 1997. “Qualitative Spatial Representation and Reasoning with the Region Connection Calculus,” GeoInformatica, 1(3):275-316.
  5. D. Dubois, M.-C. Jaulent, 1987. “A General Approach to Parameter Evaluation in Fuzzy Digital Pictures,” Pattern Recognition Letters, 6:251-59.
  6. T. Jaworski, J. Kucharski, 2010. “The Use of Fuzzy Logic for Description of Spatial Relations between Objects,” Automatyka, 14:563-80.
  7. R. Krishnapuram, J. M. Keller, Y. Ma, 1993. “Quantitative Analysis of Properties and Spatial Relations of Fuzzy Image Regions,” IEEE Trans. on Fuzzy Systems, 1(3): 222-33.
  8. H. Kwasnicka, M. Paradowski, 2005. “Spread Histogram ? A Method for Calculating Spatial Relations Between Objects,” 4th Int. Conf. on Computer Recognition Systems (CORES), Proceedings, 30:249- 56.
  9. J. Malki, E.-H. Zahzah, L. Mascarilla, 2002. “Indexation et recherche d'image fondées sur les relations spatiales entre objets,” Traitement du Signal, 18(4):235-51.
  10. P. Matsakis, D. Nikitenko, 2005. “Combined Extraction of Directional and Topological Relationship Information from 2D Concave Objects,” in M. Cobb, F. Petry, V. Robinson (Eds.), Fuzzy Modeling with Spatial Information for Geographic Problems, SpringerVerlag, 15-40.
  11. P. Matsakis, L. Wawrzyniak, J. Ni, 2010. “Relative Positions in Words: A System that Builds Descriptions Around Allen Relations,” Int. J. of Geographical Information Science, 24(1):1-23.
  12. P. Matsakis, L. Wendling, 1999. “A New Way to Represent the Relative Position of Areal Objects,” IEEE Trans. on Pattern Analysis and Machine Intelligence, 21(7):634-43.
  13. P. Matsakis, L. Wendling, J. Ni, 2010. “A General Approach to the Fuzzy Modeling of Spatial Relationships,” in R. Jeansoulin, O. Papini, H. Prade, S. Schockaert (Eds.), Methods for Handling Imperfect Spatial Information, Springer-Verlag, 49-74.
  14. K. Miyajima, A. Ralescu, 1994. “Spatial Organization in 2D Segmented Images: Representation and Recognition of Primitive Spatial Relations,” Fuzzy Sets and Systems, 65(2-3):225-36.
  15. D. Recoskie, T. Xu, P. Matsakis, 2012. “A General Algorithm for Calculating Force Histograms using Vector.
  16. Data,” 1st Int. Conf. on Pattern Recognition Applications and Methods (ICPRAM), Proceedings, 86-92.
  17. A. Rosenfeld, R. Klette, 1984. Degree of Adjacency or Surroundedness, University of Maryland, 30 pages.
  18. N. Salamat, E.-H. Zahzah, 2012a. “On the Improvement of Combined Fuzzy Topological and Directional Relations Information,” Pattern Recognition, 45(4):1559-68.
  19. N. Salamat, E.-H. Zahzah, 2012b. “Two-Dimensional Fuzzy Spatial Relations: A New Way of Computing and Representation,” Advances in Fuzzy Systems, 2012:1-15.
  20. N. Salamat, E.-H. Zahzah, 2012c. “Spatio-Temporal Reasoning by Combined Topological and Directional Relations Information,” Int. J. of Artificial Intelligence and Soft Computing, 3(2):185-201.
  21. N. Salamat, E.-H. Zahzah, 2012d. “Spatiotemporal Relations and Modeling Motion Classes by Combined Topological and Directional Relations Method,” ISRN Machine Vision, 12 pages.
  22. K.C. Santosh, L. Wendling, B. Lamiroy, 2010. “Unified Pairwise Spatial Relations: An Application to Graphical Symbol Retrieval”, in J.-M. Ogier, W. Liu, J. Llados (Eds.), Graphics Recognition. Achievements, Challenges, and Evolution, SpringerVerlag, 163-74.
  23. C.-R. Shyu, M. Klaric, G. J. Scott, A. S. Barb, C. H. Davis, K. Palaniappan, 2007. “GeoIRIS: Geospatial Information Retrieval and Indexing System ? Content Mining, Semantics Modeling, and Complex Queries,” IEEE Trans. on Geoscience and Remote Sensing, 45(4):839-52.
  24. M. Skubic, D. Perzanowski, S. Blisard, A. Schultz, W. Adams, M. Bugajska, D. Brock, 2004. “Spatial Language for Human-Robot Dialogs,” IEEE Trans. on Systems, Man, and Cybernetics (Part C), 34(2):154-67.
  25. Z. Wang, 2013. “A New Quadtree Histogram-Based Spatial.
  26. Modeling Based on Cloud Model,” Int. J. of Hybrid Information Technology, 6(6):31-40.
  27. Y. Wang, F. Makedon, 2003. “R-Histogram: Quantitative Representation of Spatial Relations for SimilarityBased Image Retrieval,” ACM Int. Multimedia Conf. and Exhibition (MM), Proceedings, 323-6.
  28. Y. Wang, F. Makedon, A. Chakrabarti, 2004. “R*- Histograms: Efficient Representation of Spatial Relations between Objects of Arbitrary Topology,” 12th Annual Int. Conf. on Multimedia (MM), Proceedings, 356-9.
  29. W. Wang, B. Xiong, H. Sun, H. Cai, Y. Jiang, G. Kuang, 2012. “An Affine Invariant Relative Attitude Relationship Descriptor for Shape Matching Based on Ratio Histograms,” EURASIP J. on Advances in Signal Processing, 2012(1):1-10.
  30. K. Zhang, T. Liu, Z. Li, W. Zhao, 2014. “A New Directional Relation Model,” Int. J. of Signal Processing, Image Processing & Pattern Recognition, 7(2):237-48.
  31. K. Zhang, K. Wang, X. Wang, Y. Zhong, 2010. “Spatial Relations Modeling Based on Visual Area Histogram,” 11th ACIS Int. Conf. on Software Engineering Artificial Intelligence Networking and Parallel/Distributed Computing (SNPD), Proceedings, 97-101.
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Paper Citation


in Harvard Style

Naeem M. and Matsakis P. (2015). Relative Position Descriptors - A Review . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 286-295. DOI: 10.5220/0005211002860295


in Bibtex Style

@conference{icpram15,
author={Mohammad Naeem and Pascal Matsakis},
title={Relative Position Descriptors - A Review},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={286-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005211002860295},
isbn={978-989-758-076-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Relative Position Descriptors - A Review
SN - 978-989-758-076-5
AU - Naeem M.
AU - Matsakis P.
PY - 2015
SP - 286
EP - 295
DO - 10.5220/0005211002860295