A SPACE- AND TIME-EFFICIENT MOSAIC-BASED ICONIC MEMORY FOR INTERACTIVE SYSTEMS

Birgit Möller, Stefan Posch

Abstract

One basic capability of interactive and mobile systems to cope with unknown situations and environments is active, sequence-based visual scene analysis. Image sequences provide static as well as dynamic and also 2D as well as 3D information about a certain scene. However, at the same time they require efficient mechanisms to handle their large data volumes. In this paper we introduce a new concept of a visual scene memory for interactive mobile systems that supports these systems with a space- and time-efficient data structure for representing iconic information. The memory is based on a new kind of mosaic images called multi-mosaics and allows to efficiently store and process sequences of stationary rotating and zooming cameras. Its main key features are polytopial reference coordinate frames and an online data processing strategy. The polytopes provide euclidean coordinates and thus allow the application of standard image analysis algorithms directly to the data yielding easy access and analysis, while online data processing preserves system interactivity. Additionally, mechanisms are included to properly handle multi-resolution data and to deal with dynamic scenes. The concept has been implemented in terms of an integrated system that can easily be included as an additional module in the architecture of interactive and mobile systems. As one prototypical example for possible fields of application the integration of the memory into the architecture of an interactive multi-modal robot is discussed emphasizing the practical relevancy of the new concept.

References

  1. Bergen, J., Anandan, P., Hanna, K., and R.Hingorani (1992). Hierarchical model-based motion estimation. In ECCV, pages 237-252.
  2. Bishop, G. and McMillan, L. (1995). Plenoptic modeling: An image-based rendering system. In SIGGRAPH Computer Graphics Proceedings, pages 39-46. Annual Conference Series.
  3. Burt, P. and Anandan, P. (1994). Image stabilization by registration to a reference mosaic. In Image Understanding Workshop, pages 1:425-434, Monterey, CA.
  4. Capel, D. (2004). Image Mosaicing and Super-resolution. Springer.
  5. Coorg, S. and Teller, S. (2000). Spherical mosaics with quaternions and dense correlation. International Journal of Computer Vision, 37(3):259-273.
  6. Davis, J. (1998). Mosaics of scenes with moving objects. In CVPR, pages (1):97-100, Santa Barbara, USA.
  7. de Agapito, L., Hartley, R., and Hayman, E. (1999). Linear self-calibration of a rotating and zooming camera. In IEEE Int. Conference on Computer Vision and Pattern Recognition, pages 15-21.
  8. Hartley, R. and Zisserman, A. (2000). Multiple View Geometry in Computer Vision. Cambridge University Press.
  9. Ishiguro, H. and Tsuji, S. (1996). Image-based memory of environment. In Proc. of Int. Conf. on Intelligent Robots and Systems (IROS 7896), pages 634-639.
  10. Mann, S. and Picard, R. (1996). Video orbits of the projective group: A new perspective on image mosaicing. Technical Report 338, MIT Media Laboratory Perceptual Computing Section.
  11. Möller, B. and Posch, S. (2002). Analysis of object interactions in dynamic scenes. In Pattern Recognition, Proc. of DAGM Symp., LNCS 2449, pages 361-369, Zurich, Swiss. Springer.
  12. Möller, B., Posch, S., Haasch, A., Fritsch, J., and Sagerer, G. (2005). Interactive object learning for robot companions using mosaic images. In Proc. of Int. Conf. on Intelligent Robots and Systems (IROS), pages 371- 376, Edmonton, Canada.
  13. Peleg, S., Rousso, B., Rav-Acha, A., and Zomet, A. (2000). Mosaicing on adaptive manifolds. PAMI, 22(10):1144-1154.
  14. Sawhney, H. S., Hsu, S., and Kumar, R. (1998). Robust video mosaicing through topology inference and local to global alignment. In ECCV, pages 103-119, Freiburg.
  15. Shum, H.-Y. and Szeliski, R. (2000). Systems and experiment paper: Construction of panoramic image mosaics with global and local alignment. IJCV, 36(2):101-130.
  16. Teller, S. (1998). Toward urban model acquisition from geolocated images. In Proc. of Pacific Graphics, pages 45-51, Singapore.
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Paper Citation


in Harvard Style

Möller B. and Posch S. (2006). A SPACE- AND TIME-EFFICIENT MOSAIC-BASED ICONIC MEMORY FOR INTERACTIVE SYSTEMS . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 413-421. DOI: 10.5220/0001375204130421


in Bibtex Style

@conference{visapp06,
author={Birgit Möller and Stefan Posch},
title={A SPACE- AND TIME-EFFICIENT MOSAIC-BASED ICONIC MEMORY FOR INTERACTIVE SYSTEMS},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={413-421},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001375204130421},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - A SPACE- AND TIME-EFFICIENT MOSAIC-BASED ICONIC MEMORY FOR INTERACTIVE SYSTEMS
SN - 972-8865-40-6
AU - Möller B.
AU - Posch S.
PY - 2006
SP - 413
EP - 421
DO - 10.5220/0001375204130421