SPATIO-TEMPORAL BLOCK MODEL FOR VIDEO INDEXATION ASSISTANCE

Alain Simac-Lejeune, Michéle Rombaut, Patrick Lambert

2010

Abstract

In the video indexing framework, we have developed an assistance system for the user to define a new concept as semantic index according to the features automatically extracted from the video. Because the manual indexing is a long and tedious task, we propose to focus the attention of the user on pre selected prototypes that a priori correspond to the concept. The proposed system is decomposed in three steps. In the first one, some basic spatio-temporal blocks are extracted from the video, a particular block is associated to a particular property of one feature. In the second step, a Question/Answer system allows the user to define links between basic blocks in order to define concept block models. And finally, some concept blocks are extracted and proposed as prototypes of the concepts. In this paper, we present the two first steps, particularly the block structure, illustrated by an example of video indexing that corresponds to the concept running in athletic videos.

References

  1. Ayache, S. and Quénot, G. (2008). LIG and LIRIS at TRECVID 2008: High Level Feature Extraction and Collaborative Annotation. In TRECVID Workshop, Gaithersburg, MD, USA.
  2. Bouguet, J.-Y. (2000). Pyramidal implementation of the lucas kanade feature tracker description of the algorithm.
  3. Burgener, R. (2006). Artificial neural network guessing method and game - European Patent EP 1710735 (A1).
  4. Csurka, G., Dance, C. R., Fan, L., Willamowski, J., and Bray, C. (2004). Visual categorization with bags of keypoints. In ECCV International Workshop on Statistical Learning in Computer Vision.
  5. Duda, R. O. and Hart, P. (1972). Use of the Hough transformation to detect lines and curves in pictures. ACM, 15:11-15.
  6. Harris, C. and Stephens, M. (1988). A combined corner and edge detector. In The Fourth Alvey Vision Conference, pages 147-151.
  7. Laptev, I. and Lindeberg, T. (2003). Space-time interest points. ICCV'03, pages 432-439.
  8. Odobez, J. and Bouthemy, P. (1995). Robust multiresolution estimation of parametric motion models. Journal of Visual Communication and Image Representation, 6(4):348-365.
  9. Sivic, J. and Zisserman, A. (2003). Video Google: A text retrieval approach to object matching in videos. Proceedings of the International Conference on Computer Vision.
  10. Valet, L., Mauris, G., Bolon, P., and Keskes, N. (2003). A fuzzy rule-based interactive fusion system for seismic data analysis. 4(2):123-133.
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Paper Citation


in Harvard Style

Simac-Lejeune A., Rombaut M. and Lambert P. (2010). SPATIO-TEMPORAL BLOCK MODEL FOR VIDEO INDEXATION ASSISTANCE . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 475-480. DOI: 10.5220/0003098904750480


in Bibtex Style

@conference{kdir10,
author={Alain Simac-Lejeune and Michéle Rombaut and Patrick Lambert},
title={SPATIO-TEMPORAL BLOCK MODEL FOR VIDEO INDEXATION ASSISTANCE},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={475-480},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003098904750480},
isbn={978-989-8425-28-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - SPATIO-TEMPORAL BLOCK MODEL FOR VIDEO INDEXATION ASSISTANCE
SN - 978-989-8425-28-7
AU - Simac-Lejeune A.
AU - Rombaut M.
AU - Lambert P.
PY - 2010
SP - 475
EP - 480
DO - 10.5220/0003098904750480