Automatic Directions for Object Localization in Virtual Environments

  • Graciela Lara
  • Angélica De Antonio
  • Adriana Peña
  • Mirna Muñoz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 746)


In order to assist users in the process of locating objects in Virtual Environments (VE), we automatize the process of giving directions through a computational model. This model generates directions in natural language by using spatial and perceptual aspects. It involves three main processes: (1) a computational model of perceptual saliency for 3D objects; (2) a user model and an explicit representation of virtual world semantics; and (3) the algorithm for automatic generation of directions to locate objects in natural language. Reference frames and reference objects support the model. For the selection of the best reference 3D object are considered three criteria: the perceptual saliency of the objects, the probability of the user to remember the object location, and prior knowledge from the user about the object. This paper presents the structure and the processes of the proposed model.


Saliency User modeling Virtual Reality Spatial language Natural language generation Spatial location Reference object  Data ontology 


  1. 1.
    McNamara, T.P.: How are the locations of objects in the environment represented in memory? In: Spatial Cognition III. Lecture Notes in Computer Science, vol. 2685, pp. 174–191. Springer (2003)Google Scholar
  2. 2.
    Gapp, K.-P.: Processing spatial relations in object localization tasks, pp. 1–7. Universität des Saarlandes, Federal Republic of Germany (1996a)Google Scholar
  3. 3.
    Barclay, M.: Reference object choice in spatial language: machine and human models. Ph.D. thesis. University of Exeter, p. 274 (2010)Google Scholar
  4. 4.
    Kelleher, J.D.: A perceptually based computational framework for the interpretation of spatial language. Ph.D. thesis, School of Computing, Dublin City University, Dublin, pp. 1–463 (2003)Google Scholar
  5. 5.
    Gorniak, P., Roy, D.: Grounded semantic composition for visual scenes. J. Artif. Intell. Res. 21, 429–470 (2004)Google Scholar
  6. 6.
    Trinh, T.-H.: A constraint-based approach to modelling spatial semantics of virtual environments. Ph.D. thesis, Université de Bretagne Occidentale (2013)Google Scholar
  7. 7.
    Schütte, N.: Resolving perception based problems in human-computer dialogue, pp. 1–370. School of Computing, Dublin Institute of Technology, Ireland (2016)Google Scholar
  8. 8.
    Hou, Z., Marjorie, S.: Natural spatial description generation for human-robot interaction in indoor environments. In: IEEE International Conference on Smart Computing (SMARTCOMP), pp. 1–3. IEEE (2016)Google Scholar
  9. 9.
    Lara, G., De Antonio, A., Peña, A.: Computerized spatial language generation for object location. Virtual Real. 20(3), 183–192 (2016)CrossRefGoogle Scholar
  10. 10.
    Frintrop, S., Rome, E., Christensen, H.I.: Computational visual attention systems and their cognitive foundations: a survey. ACM Trans. Appl. Percept. (TAP) 7(1), 6:1–6:39 (2010)Google Scholar
  11. 11.
    Vargas, M.L., Lahera, G.: “Asignación de relavancia”: Una propuesta para el término inglés “salience”. Actas Esp Psiquiatría 39, 271–272 (2011)Google Scholar
  12. 12.
    Lahera, G., Freund, N., Sáin-Ruíz, J.: Asignación de relevancia (salience) y desregulación del sistema dopaminérgico. Revista de Psiquiatría y Salud Mental 6(1), 45–51 (2013)CrossRefGoogle Scholar
  13. 13.
    Hall, D., Leibe, B., Schile, B.: Saliency of interest points under scale changes. In: British Machine Vision Conference (BMVC 2002), Cardiff, UK, pp. 646–655 (2002)Google Scholar
  14. 14.
    Lara, L.G., et al.: Comparative analysis of shape descriptors for 3D objects. Multimed. Tools Appl. 76(5), 6993–7040 (2017)CrossRefGoogle Scholar
  15. 15.
    Tkalčič, M., Tasič, J.F.: Colour spaces - perceptual, historical and applicational background. In: The IEEE Region 8 EUROCON 2003: Computer as a Tool, vol. 1, pp. 304–308. IEEE (2003)Google Scholar
  16. 16.
    Lara, G., De Antonio, A., Peña, A.: A computational measure of saliency of the shape of 3D objects. In: Trends and Applications in Software Engineering. Springer, Cham (2016)Google Scholar
  17. 17.
    Lara, G., et al.: 3D objects shape relevance for saliency measure. In: Trends and Applications in Software Engineering, 6th International Conference on Software Process Improvement (CIMPS 2017). Springer, México (2017)Google Scholar
  18. 18.
    Lara, G., De Antonio, A., Peña, A.: A computational model of perceptual saliency for 3D objects in virtual environment (2017, in press)Google Scholar
  19. 19.
    Bataller, S.B., Meléndez Moral, J.: Cambios en la memoria asociados al envejecimiento. Geriátrika 22(5), 179–185 (2006)Google Scholar
  20. 20.
    Craik, F.I., Lockhart, R.S.: Niveles de procesamiento: Un marco para la investigación sobre la memoria. Estudios de psicología. Taylor & Francis 1(2), 93–109 (1980)CrossRefGoogle Scholar
  21. 21.
    Mou, W., McNamara, T.P.: Intrinsic frames of reference in spatial memory. J. Exp. Psychol. Learn. Mem. Cogn. 28(1), 162–170 (2002)CrossRefGoogle Scholar
  22. 22.
    Gapp, K.-P.: Object localization: selection of optimal reference objects. In: Spatial Information Theory. A Theoretical Basis For GIS, pp. 519–536 (1995)Google Scholar
  23. 23.
    Harrington, D.O., Drake, M.V.: Los campos visuales: texto y atlas de perimetría clínica. Ediciones Científicas y Técnicas (1993)Google Scholar
  24. 24.
    Gapp, K.-P.: Selection of best reference objects in objects localizations. In: Proceedings of the AAAI Spring Symposium on Cognitive and Comutational Models of Spatial Representations, Stanford, CA (1996b)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Graciela Lara
    • 1
  • Angélica De Antonio
    • 2
  • Adriana Peña
    • 1
  • Mirna Muñoz
    • 3
  1. 1.CUCEI of the Universidad de GuadalajaraGuadalajaraMexico
  2. 2.Escuela Técnica Superior de Ingenieros Informático of the Universidad Politécnica de MadridBoadilla del MonteSpain
  3. 3.Centro de Investigación En MatemáticasZacatecasMexico

Personalised recommendations