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State-of-the-Art in Content-Based Image and Video Retrieval pp 235–254Cite as

Facial and Motion Analysis for Image and Video Retrieval

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Part of the book series: Computational Imaging and Vision ((CIVI,volume 22))

Abstract

Today’s challenge in automated image retrieval is to devise a system which is able to analyse a single or sequence of images, and extract enough information to provide a meaningful description of the scene and events presented. Computer vision has been studying this problem for some 50 years, trying to solve the general “image understanding” problem within several application domains. Many techniques have been developed to analyse images and extract an abundance of information about the captured scene. In this chapter two important features are considered: the motion in the scene and the presence of human faces. Both features provide very powerful cues to understand the image or video content thus allowing to perform an automatic annotation of data for subsequent retrieval. Several approaches are discussed leaving to the reader the customisation of the proposed techniques to a given application.

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References

  1. C.H.C. Leung and D. Sutanto, “Multimedia data modelling and management for semantic content retrieval”, Handbook of Multimedia Computing, B. Fuhrt ( Ed. ), CRC Press, 1998.

    Google Scholar 

  2. B.K.P. Horn, “Robot Vision”, MIT Press, 1988.

    Google Scholar 

  3. D.H.. Ballard and C.M. Brown, “Computer Vision”, Academic Press, 1980.

    Google Scholar 

  4. A. Rosenfeld, “Image understanding”, IEEE Computer Society press, 1990.

    Google Scholar 

  5. H. H. Nagel, “Direct estimation of optical flow and of its derivatives”, in Artificial and Biological Vision Systems, G. A. Orban and H. H. Nagel, Eds. 1992, pp. 193–224, Springer Verlag.

    Google Scholar 

  6. M. Otte and H.H. Nagel, “Estimation of optical flow based on higher order spatiotemporal derivatives in interlaced and non-interlaced image sequences”, Artificial Intelligence, vol. 78, pp. 5–43, 1995.

    Article  Google Scholar 

  7. D. Ben-Tzvi, A. Del Bimbo, and P. Nesi, “Optical flow from constraint lines parametrization”, Pattern Recognition, vol. 26, no. 10, pp. 1549–61, 1993.

    Article  Google Scholar 

  8. M. Campani and A. Verri, “Computing optical flow from an overconstrained system of linear algebraic equations”, in Proc. of 3rd IEEE Intl. Conference on Computer Vision, Osaka, Japan, 1990, pp. 22–26, IEEE.

    Google Scholar 

  9. K. Wohn, L. S. Davis, and P. Thirft, “Motion estimation based on multiple local constraints and non-linear smoothing”, Pattern Recognition, vol. 16, pp. 563–70, 1983.

    Article  Google Scholar 

  10. O. Tretiak and L. Pastor, “Velocity estimation from image sequences with second order differential operators”, in Proc. of 7th IEEE Intl. Conference on Pattern Recognition. 1984, pp. 16–19, IEEE

    Google Scholar 

  11. M. Tistarelli and G. Sandini, “Dynamic aspects in active vision”, CVGIP, Special issue on Purposive and Qualitative Active Vision, Y. Aloimonos, Ed., vol. 56, no. 1, pp. 108–129, July 1992.

    Google Scholar 

  12. J. L. Barron, D. J. Fleet, and S. S. Beauchemin, “Performance of optical flow techniques”, Int. J. of Computer Vision, vol. 12, pp. 43–77, 1994.

    Article  Google Scholar 

  13. M. Otte and H. H. Nagel, “Optical flow estimation: Advances and comparisons”, in Proc. of 3rd European Conference on Computer Vision, J. O. Eklundh, Ed., Stockholm, Sweden, May 2–6, 1994, pp. 51–60, Springer Verlag.

    Google Scholar 

  14. J. Weber and J. Malik, “Robust computation of optical flow in a multi-scale differential framework”, Int. J. of Computer Vision, vol. 14, pp. 6781, 1995.

    Article  Google Scholar 

  15. S. Uras, F. Girosi, A. Verri, and V. Torre, “A computational approach to motion perception”, Biological Cybernetics, vol. 60, pp. 79–87, 1988.

    Article  Google Scholar 

  16. A. Verri and T. Poggio, “Motion field and optical flow: qualitative properties”, IEEE Trans. on PAM’, vol. PAMI-11, no. 5, pp. 490–498, 1989.

    Article  Google Scholar 

  17. H. H. Nagel and W Enkelmann, “An investigation of smoothness constraints for the estimation of displacement vector fields from image sequences”, IEEE Trans. on PAMI, vol. PAMI-8, no. 1, pp. 565–593, 1986.

    Article  Google Scholar 

  18. Facial and Motion Analysis for Image and Video Retrieval 253

    Google Scholar 

  19. H. H. Nagel, “On the estimation of optical flow: Relations between differenet approaches and some new results”, Artificial Intelligence, vol. 33, pp. 299–324, 1987.

    Article  Google Scholar 

  20. M. Tistarelli, “Multiple Constraints to Compute Optical Flow”, IEEE Trans. on PAMI, Vol. 18, No 12, pp 1243–1250, 1996.

    Article  Google Scholar 

  21. J. R. Bergen, P. Anandan, K. J. Hanna, and R. Hingorani, “Hierarchical model-based motion estimation”, in Proc. of 2nd European Conference on Computer Vision, G. Sandini, Ed., S. Margherita Ligure, Italy, May 19–22, 1992, pp. 237–252, Springer Verlag.

    Google Scholar 

  22. A. Verri, F. Girosi, and V. Torre, “Differential techniques for optical flow”, Journal of the Optical Society of America A, vol. 7, pp. 912–922, 1990.

    Article  Google Scholar 

  23. M. Tistarelli and G. Sandini, “Estimation of depth from motion using an anthropomorphic visual sensor”, Image and Vision Computing, vol. 8, no. 4, pp. 271–278, 1990.

    Article  Google Scholar 

  24. B. K. P. Horn and B. G. Schunck, “Determining optical flow”, Artificial Intelligence, vol$117, no. 1–3, pp. 185–204, 1981.

    Google Scholar 

  25. H. H. Nagel, G. Socher, H. Kollnig, and M. Otte, “Motion boundary detection in image sequences by local stochastic tests”, in Proc. of 3rd European Conference on Computer Vision, J. O. Eklundh, Ed., Stockholm, Sweden, May 2–6, 1994, pp. 305–316, Springer Verlag.

    Google Scholar 

  26. M. Irani and P. Anandan, “Video indexing based on mosaic representation”, IEEE Trans. on PAMI, Vol 86, No 5, pp 905–21, 1998.

    Google Scholar 

  27. J.J. Little and J.E. Boyd, “Recognizing people by their gate:the shape of motion”, Videre, vol. 1, no. 2, 1998.

    Google Scholar 

  28. R. Fablet and P. Bouthemy, “Motion-based feature extraction and ascendant hierarchical classification for video indexing and retrieval”, Proc. of 3rd Intl Conference on Visual Information and Information Systems, pp 220–8, June 1999.

    Google Scholar 

  29. A. Blake and M. Isard, “Condensation - conditional density propagation for visual tracking”, Int. Journal of Computer Vision, vol. 29, no. 1, pp 528, 1998.

    Google Scholar 

  30. R. Nelson and R. Polana, “Qualitative recognition of motion using temporal texture”, Computer Vision Graphics and Image Processing: Image Understanding, Vol 56, No 1, pp 78–99, 1992.

    MATH  Google Scholar 

  31. G. Robertson and I. Craw. “Testing face recognition systems”, In Proc. of 4th British Machine Vision Conference, pp 2534, University of Surrey, Guildford (UK), 1993.

    Google Scholar 

  32. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman, “Eigenfaces vs. fisherfaces: Recognition using class specific linear projection”, IEEE Trans. on PAMI, PAMI-19(7): 711–20, 1997.

    Google Scholar 

  33. Massimo Tistarelli, Enrico Grosso

    Google Scholar 

  34. R.C. Tryon and D.E. Bailey, Cluster Analysis, Mc Graw-Hill, New York, USA, 1970.

    Google Scholar 

  35. B.Scholkopf, K.K. Sung, C.J.C. Burges, F. Girosi, P. Niyogi, T. Poggio, and V. Vapnik, “Comparing support vector machines with gaussian kernels to radial basis function classifiers”, IEEE Trans. on Signal Processing, 45 (11): 2758–65, 1997.

    Article  Google Scholar 

  36. Active/Space-Variant Object Recognition”, Image and Vision Computing, Vol. 13, No 3, pp 215–226, April 1995.

    Google Scholar 

  37. Tistarelli, M. and Grosso, E. (1999) “Active vision-based face authentication”, Image and Vision Computing, M. Tistarelli (Ed.), special issue on “Facial Image Analysis”, 1999.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Vision Laboratory, University of Genoa — DIST, Via Opera Pia 13, 16145, Genoa, Italy

    Massimo Tistarelli & Enrico Grosso

Authors
  1. Massimo Tistarelli
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  2. Enrico Grosso
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Editor information

Editors and Affiliations

  1. Utrecht University, The Netherlands

    Remco C. Veltkamp

  2. University of Freiburg, Germany

    Hans Burkhardt

  3. University of Munich, Germany

    Hans-Peter Kriegel

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© 2001 Springer Science+Business Media Dordrecht

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Tistarelli, M., Grosso, E. (2001). Facial and Motion Analysis for Image and Video Retrieval. In: Veltkamp, R.C., Burkhardt, H., Kriegel, HP. (eds) State-of-the-Art in Content-Based Image and Video Retrieval. Computational Imaging and Vision, vol 22. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9664-0_11

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  • DOI: https://doi.org/10.1007/978-94-015-9664-0_11

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5863-8

  • Online ISBN: 978-94-015-9664-0

  • eBook Packages: Springer Book Archive

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