Abstract
Service robots need to be able to recognize objects located in complex environments. Although there has been recent progress in this area, it remains difficult for autonomous vision systems to recognize objects in natural conditions. Thus we propose an interactive object recognition system, which asks the user to verbally provide information about the objects that it cannot recognize. However, humans may use various expressions to describe objects. Meanwhile, the same verbal expression may indicate different meanings depending on the situation. Thus we have examined human descriptions of object shapes through experiments using human participants. This paper presents the findings from the experiments useful in designing interactive object recognition systems.
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
Lowe, D.G.: Distinctive Image Features from Scale-invariant Keypoints. International Journal on Computer Vision 20(2), 91–110 (2004)
Ponce, J., Hebert, M., Schmid, C., Zisserman, A. (eds.): Toward Category-Level Object Recognition. LNCS, vol. 4170. Springer, Heidelberg (2006)
Kurnia, R., Hossain, M.A., Nakamura, A., Kuno, Y.: Generation of Efficient and User-Friendly Queries for Helper Robots to Detect Target Objects. Advanced Robotics 20(5), 499–517 (2006)
Mansur, A., Sakata, K., Kobayashi, Y., Kuno, Y.: Human Robot Interaction through Simple Expressions for Object Recognition. In: Proc. 17th IEEE RO-MAN, pp. 647–652 (2008)
Cao, L., Kobayashi, Y., Kuno, Y.: Spatial Relation Model for Object Recognition in Human-robot Interaction. In: Huang, D.-S., Jo, K.-H., Lee, H.-H., Kang, H.-J., Bevilacqua, V. (eds.) ICIC 2009. LNCS, vol. 5754, pp. 574–584. Springer, Heidelberg (2009)
Winograd, T.: Understanding Natural Language. Academic Press, New York (1972)
Kawaji, T., Okada, K., Inaba, M., Inoue, H.: Human Robot Interaction through Integrating Visual Auditory Information with Relaxation Method. In: IEEE Int. Conf. Multisensor Fusion on Integration for Intelligent Systems, pp. 323–328 (2003)
McGuire, P., Fritsch, J., Steil, J.J., Roothling, F., Fink, G.A., Wachsmuth, S., Sagerer, G., Ritter, H.: Multi-modal Human Machine Communication for Instruction Robot Grasping Tasks. In: Proc. IROS 2002, pp. 1082–1089 (2002)
Takizawa, M., Makihara, Y., Shimada, N., Miura, J., Shirai, Y.: A Service Robot with Interactive Vision- objects Recognition Using Dialog with User. In: Proc. First Int. Workshop Language Understanding and Agents for Real World Interaction (2003)
Thurstone, L.L.: The Method of Paired Comparisons for Social Values. Journal of Abnormal and Social Psychology 21, 384–400 (1927)
Kuno, Y., Sakata, K., Kobayashi, Y.: Object recognition in Service Robots: Conducting Verbal Interaction on Color and Spatial Relationship. In: Proc. IEEE 12th ICCV Workshops (Human-Computer Interaction), pp. 2025–2031 (2009)
Kinect, http://www.xbox.com/en-US/kinect
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mori, S., Kobayashi, Y., Kuno, Y. (2011). Understanding the Meaning of Shape Description for Interactive Object Recognition. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-24728-6_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24727-9
Online ISBN: 978-3-642-24728-6
eBook Packages: Computer ScienceComputer Science (R0)