Abstract
This paper presents the concept and an evaluation of a novel approach to support students to understand complex spatial relations and to learn unknown terms of a domain-specific terminology with coordinated textual descriptions and illustrations. Our approach transforms user interactions into queries to an information retrieval system. By selecting text segments or by adjusting the view to interesting domain objects, learners can request additional contextual information. Therefore, the system uses pre-computed multi-level representations of the content of explanatory text and of views on 3D models to suggest textual descriptions or views on 3D objects that might support the current learning task.
Our experimental application is evaluated by a user study that analyzes (i) similarity measures that are used by the information retrieval system to coordinate the content of descriptive texts and computer-generated illustrations and (ii) the impact of the individual components of these measures. Our study revealed that the retrieved results match the preferences of the users. Furthermore, the statistical analysis suggests a rough value to cut-off retrieval results according to their relevancy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Blanz, V., Tarr, M.J., Bülthoff, H.H.: What Object Attributes Determine Canonical Views? Perception 28, 575–599 (1999)
Digimation Inc. Viewpoint 3D Library (2007)
Gray, H.: Anatomy of the Human Body, 20th edn. Lea & Febiger, Philadelphia (1918)
Götzelmann, T., Vázquez, P.-P., Hartmann, K., Germer, T., Nürnberger, A., Strothotte, T.: Mutual Text-Image Queries. Preprint 1/2007, Department of Computer Science, Otto-von-Guericke University of Magdeburg (2007)
Kamada, T., Kawai, S.: A Simple Method for Computing General Position in Displaying Three-Dimensional Objects. Computer Vision, Graphics, and Image Processing 41(1), 43–56 (January 1988)
Mühler, K., Neugebauer, M., Tietjen, C., Preim, B.: Viewpoint Selection for Intervention Planning. In: EG/IEEE-VGTC Symp. on Visualization (to appear, 2007)
National Library of Medicine.Visible Human Project (2007)
Palmer, S.E., Rosch, E., Chase, P.: Canonical Perspective and the Perception of Objects. In: J., L., A., B. (eds.) Attention and Performance, vol. 9, pp. 135–151. Erlbaum, Hillsdale (1981)
Plemenos, D., Benayada, M.: Intelligent Display in Scene Modeling. New Techniques to Automatically Compute Good Views. In: Int. Conf. on Computer Graphics & Vision (GraphiCon’96) (1996)
Salton, G., Allan, J., Buckley, C., Singhal, A.: Automatic Analysis, Theme Generation, and Summarization of Machine-Readable Texts. Science 264, 1421–1426 (1994)
Salton, G., Wong, A., Yang, C.S.: A Vector Space Model for Automatic Indexing. Communications of the ACM 18(11), 613–620 (1975)
Viola, I., Feixas, M., Sbert, M., Gröller, M.E.: Importance-Driven Focus of Attention. IEEE Transactions on Visualization and Computer Graphics 12(5), 933–940 (2006)
Vázquez, P.-P., Feixas, M., Sbert, M., Heidrich, W.: Viewpoint selection using viewpoint entropy. In: Vision Modeling and Visualization Conference (VMV-01), pp. 273–280 (2001)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Götzelmann, T., Vázquez, PP., Hartmann, K., Nürnberger, A., Strothotte, T. (2007). Correlating Text and Images: Concept and Evaluation. In: Butz, A., Fisher, B., Krüger, A., Olivier, P., Owada, S. (eds) Smart Graphics. SG 2007. Lecture Notes in Computer Science, vol 4569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73214-3_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-73214-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73213-6
Online ISBN: 978-3-540-73214-3
eBook Packages: Computer ScienceComputer Science (R0)