Interest-Point-Based Landmark Computation for Agents’ Spatial Description Coordination
J. I. Olszewska
2016
Abstract
In applications involving multiple conversational agents, each of these agents has its own view of a visual scene, and thus all the agents must establish common visual landmarks in order to coordinate their space understanding and to coherently share generated spatial descriptions of this scene. Whereas natural language processing approaches contribute to define the common ground through dialogues between these agents, we propose in this paper a computer-vision system to determine the object of reference for both agents efficiently and automatically. Our approach consists in processing each agent’s view by computing the related, visual interest points, and then by matching them in order to extract the salient and meaningful landmark. Our approach has been successfully tested on real-world data, and its performance and design allow its use for embedded robotic system communication.
References
- Alqaisi, T., Gledhill, D., and Olszewska, J. I. (2012). Embedded double matching of local descriptors for a fast automatic recognition of real-world objects. In Proceedings of the IEEE International Conference on Image Processing (ICIP'12), pages 2385-2388.
- Alsuqayhi, A. and Olszewska, J. I. (2013). Efficient optical character recognition system for automatic soccer player's identification. In Proceedings of the IAPR International Conference on Computer Analysis of Images and Patterns Workshop (CAIP'13), pages 139- 150.
- Anacta, V. J. A., Schwering, A., and Li, R. (2014). Determining hierarchy of landmarks in spatial descriptions. In Proceedings of the International Conference on Geographic Information Science (GIScience'14).
- Bhat, M. and Olszewska, J. I. (2014). DALES: Automated tool for detection, annotation, labelling and segmentation of multiple objects in multi-camera video streams. In Proceedings of the ACL International Conference on Computational Linguistics (COLING'14), pages 87-94.
- Jurafsky, D. and Martin, J. H. (2000). Dialogue and conversational agents, chapter 19, pages 719-761. Prentice Hall.
- Levinson, S. C. (2003). Space in Language and Cognition: Explorations in Cognitive Diversity, chapter 5. Cambridge Press University.
- Ma, Y., Raux, A., Ramachandran, D., and Gupta, R. (2012). Landmark-based location belief tracking in a spoken dialog system. In Proceedings of the Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL'12), pages 169-178.
- Olszewska, J. I. (2011). Spatio-Temporal Visual Ontology. In Proceedings of the 1st EPSRC/BMVA Workshop on Vision and Language (VL'11).
- Olszewska, J. I. (2012). A new approach for automatic object labeling. In Proceedings of the 2nd EPSRC/BMVA Workshop on Vision and Language (VL'12).
- Olszewska, J. I. (2013). Clock-modeled ternary spatial relations for visual scene analysis. In Proceedings of the ACL International Conference on Computational Semantics Workshop, pages 20-30.
- Olszewska, J. I. (2015a). 3D Spatial reasoning using the clock model. Research and Development in Intelligent Systems XXXII, Springer, pages 147-154.
- Olszewska, J. I. (2015b). “Where is my cup?” - Fully automatic detection and recognition of textureless objects in real-world images. Lectures Notes in Computer Science, Springer, 9256:501-512.
- Olszewska, J. I. and McCluskey, T. L. (2011). Ontologycoupled active contours for dynamic video scene understanding. In Proceedings of the IEEE International Conference on Intelligent Engineering Systems, pages 369-374.
- Summers-Stay, D., Cassidy, T., and Voss, C. R. (2014). Joint navigation in commander/robot teams: Dialog and task performance when vision is bandwidthlimited. In Proceedings of the ACL International Conference on Computational Linguistics, pages 9-16.
- Watson, M. E., Pickering, M. J., and Branigan, H. P. (2004). Alignment of reference frames in dialogue. In Proceedings of the Annual Conference of the Cognitive Science Society.
- Zhanga, X., Lia, Q.-Q., Fang, Z.-X., Lu, S.-W., and Shaw, S.-L. (2014). An assessment method for landmark recognition time in real scenes. Journal of Environmental Psychology, 40:206-217.
Paper Citation
in Harvard Style
Olszewska J. (2016). Interest-Point-Based Landmark Computation for Agents’ Spatial Description Coordination . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 566-569. DOI: 10.5220/0005847705660569
in Bibtex Style
@conference{icaart16,
author={J. I. Olszewska},
title={Interest-Point-Based Landmark Computation for Agents’ Spatial Description Coordination},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={566-569},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005847705660569},
isbn={978-989-758-172-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Interest-Point-Based Landmark Computation for Agents’ Spatial Description Coordination
SN - 978-989-758-172-4
AU - Olszewska J.
PY - 2016
SP - 566
EP - 569
DO - 10.5220/0005847705660569