Image Mining for Infomobility

Massimo Magrini, Davide Moroni, Christian Nastasi, Paolo Pagano, Matteo Petracca, Gabriele Pieri, Claudio Salvadori, Ovidio Salvetti

2010

Abstract

The wide availability of embedded sensor platforms and low-cost camera sensors – together with the developments in wireless communication – make it now possible the conception of pervasive intelligent systems based on vision. Such systems may be understood as distributed and collaborative sensor networks, able to produce, aggregate and process images in order to mine the observed scene and communicate the relevant information found about it. In this paper, we investigate the peculiarities of visual sensor networks with respect to standard vision systems and we identify possible strategies to tackle the image mining problem. We argue that multi-node processing methods may be envisaged to decompose a complex task into a hierarchy of computationally simpler problems to be solved over the nodes of the network. We illustrate these ideas by describing an application of visual sensor network to infomobility.

References

  1. Soro, S., Heinzelman, W.: A survey of visual sensor networks. Advances in Multimedia (2009) Article ID 640386, 21 pages
  2. Adam, A., Rivlin, E., Shimshoni, I., Reinitz, D.: Robust real-time unusual event detection using multiple fixed-location monitors. IEEE Trans. PAMI 30 (2008) 555-560
  3. Colantonio, S. et al.: An intelligent and integrated platform for supporting the management of chronic heart failure patients, Computers in Cardiology (2008) 897 - 900
  4. Salvetti, O., Cetin, E.A., Pauwels, E.: Special issue on human-activity analysis in multimedia data. Eurasip Journal on Advances in Signal Processing (2008) article n. 293453
  5. Pagano, P., Piga, F., Lipari, G., Liang, Y.: Visual tracking using sensor networks. In: Proc. 2nd Int. Conf. Simulation Tools and Techniques, ICST (2009) 1-10
  6. Kundur, D., Lin, C.Y., Lu, C.S.: Visual sensor networks. EURASIP Journal on Advances in Signal Processing Signal Processing 2007 (2007) Article ID 21515, 3 pages
  7. Feng, W., Code, B., Kaiser, E.C., Shea, M., chang Feng, W., Bavoil, L.: Panoptes: scalable low-power video sensor networking technologies. In: ACM Multimedia. (2003) 562-571
  8. Hengstler, S. et al.: Mesheye: a hybrid-resolution smart camera mote. In: Proc. 6th Int. Conf. Inf. proc. in sensor networks, ACM (2007) 360-369
  9. Rowe, A. et al.: CMUcam3: An open programmable embedded vision sensor. Technical Report CMU-RI-TR-07-13, Robotics Institute, Pittsburgh, PA (2007)
  10. Chen, P. et al.: Citric: A low-bandwidth wireless camera network platform. In: Distributed Smart Cameras. (2008) 1-10
  11. Remagnino, P., Shihab, A.I., Jones, G.A.: Distributed intelligence for multi-camera visual surveillance. Pattern Recognition 37 (2004) 675-689
  12. Radke, R.J., Andra, S., Al-Kofahi, O., Roysam, B.: Image change detection algorithms: a systematic survey. IEEE Transactions on Image Processing 14 (2005) 294-307
  13. Yan, T., Ganesan, D., Manmatha, R.: Distributed image search in camera sensor networks. In Abdelzaher, T.F., Martonosi, M., Wolisz, A., eds.: SenSys, ACM (2008) 155-168
  14. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60 (2004) 91-110
  15. Viola, P.A., Jones, M.J.: Robust real-time face detection. International Journal of Computer Vision 57 (2004) 137-154
  16. Pagano, P., Piga, F., Liang, Y.: Real-time multi-view vision systems using WSNs. In: Proc. ACM Symp. Applied Comp., ACM (2009) 2191-2196
  17. IPERMOB: A Pervasive and Heterogeneous Infrastructure to control Urban Mobility in Real-Time. http://www.ipermob.org/ (2010) Last retrieved Feb 25, 2010.
Download


Paper Citation


in Harvard Style

Magrini M., Moroni D., Nastasi C., Pagano P., Petracca M., Pieri G., Salvadori C. and Salvetti O. (2010). Image Mining for Infomobility . In Proceedings of the Third International Workshop on Image Mining Theory and Applications - Volume 1: IMTA, (VISIGRAPP 2010) ISBN 978-989-674-030-6, pages 35-44. DOI: 10.5220/0002962000350044


in Bibtex Style

@conference{imta10,
author={Massimo Magrini and Davide Moroni and Christian Nastasi and Paolo Pagano and Matteo Petracca and Gabriele Pieri and Claudio Salvadori and Ovidio Salvetti},
title={Image Mining for Infomobility},
booktitle={Proceedings of the Third International Workshop on Image Mining Theory and Applications - Volume 1: IMTA, (VISIGRAPP 2010)},
year={2010},
pages={35-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002962000350044},
isbn={978-989-674-030-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Workshop on Image Mining Theory and Applications - Volume 1: IMTA, (VISIGRAPP 2010)
TI - Image Mining for Infomobility
SN - 978-989-674-030-6
AU - Magrini M.
AU - Moroni D.
AU - Nastasi C.
AU - Pagano P.
AU - Petracca M.
AU - Pieri G.
AU - Salvadori C.
AU - Salvetti O.
PY - 2010
SP - 35
EP - 44
DO - 10.5220/0002962000350044