Abstract
Relations among temporal intervals can be used to detect semantic events in audio visual documents. The aim of our work is to study all the relations that can be observed between different segmentations of a same document. These segmentations are automatically provided by a set of tools. Each tool determines temporal units according to specific low or mid-level features. All this work is achieved without any prior information about the document type (sport, news ...), its structure, or the type of the semantic events we are looking for. Considering binary temporal relations between each couple of segmentations, a parametric representation is proposed. Using this representation, observations are made about temporal relation frequencies. When using relevant segmentations, some semantic events can be inferred from these observations. If they are not relevant enough, or if we are looking for semantic events of a higher level, conjunctions between two temporal relations can turn to be more efficient. In order to illustrate how observations can be made in the parametric representation, an example is given using Allen’s relations. Finally, we present some first results of an experimental phase made on TV news programs.
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Tovinkere, V., Qian, R.J.: Detecting Semantic Events in Soccer Games: Toward a Complete Solution. In: Proc. ICME 2001, Tokyo, Japan, August 2001, pp. 1040–1043 (2001)
Bonzanini, A., Leonardi, R., Migliorati, P.: Exploitation of Temporal Dependencies of Descriptors to Extract Semanic information. DEA - University of Brescia, Via Branze, 38– 25123, Brescia, Italy
Xie, L., Chang, S.-F., Divakaran, A., Sun, H.: Structure analysis of soccer video with Hidden Markov Models. In: Proc. IEEE Int’l. Conf. on Acoustics, Speech, and Signal Processing (ICASSP) (2002)
Avrithis, Y., Tsapatsoulis, N., Kollias, S.: Broadcast News Parsing Using Visual Cues: A Robust Face Detection Approach. In: IEEE International Conference on Multimedia and Expo, New York City, NY (July 2000)
Zhou, W., Vellaikal, A., Kuo, C.-C.J.: Rule-based Video Classification System for Basketball Video Indexing. In: ACM Mult. Conf. (2000)
Rui, Y., Gupta, A., Acero, A.: Automatically extracting highlights for TV baseball programs. In: Proc. ACM Multimedia 2002, Los Angeles, CA, USA, pp. 105–115 (2000)
Lefevre, S., Maillard, B., Vincent, N.: 3 classes segmentation for analysis of football audio sequences. In: Proc. ICDSP 2002, Santorin, Greece (July 2002)
Eickeler, S., Muller, S.: Content-Based Video Indexing of TV Broadcast News Using Hidden Markov Models. In: Proc. IEEE ICASSP, Phoenix (1999)
Han, M., Hua, W., Xu, W., Gong, Y.: An integrated baseball digest system using maximum entropy method. In: Proc. ACM Multimedia 2002, Juan Les Pins, France (December 2002)
Petrovic, M., Mihajlovic, V., Jonker, W., Djordievic-Kajan, S.: Multi-modal extraction of highlights from tv formula 1 programs. In: Proc. ICME 2002, Lausanne, Switzerland (August 2002)
Duan, L., Xu, M., Yu, X.-D., Tian, Q.: A unified framework for semantic shot classification in sports videos. In: Proceedings of the tenth ACM international conference on Multimedia, Juan-les-Pins, France, December 01-06 (2002)
Hayes, P.: 1996. A Catalog of temporal theories. Technical report UIUC-BI-AI- 96-01, University of Illinois (1995)
Chittaro, L., Montanari, A.: Trends in Temporal Representation and Reasoning. The Knowledge Engineering Review 11(3), 281–288 (1996)
Chittaro, L., Montanari, A.: Temporal Representation and Reasoning in Artificial Intelligence: Issues and Approaches. Annals of Mathematics and Artificial Intelligence 28, 47–106 (2000)
Vila, L.: A Survey on Temporal Reasoning in Artificial Intelligence. Artificial Intelligence Communications 7(1), 4–28 (1994)
Pani, A.K.: Temporal representation and reasoning in artificial intelligence: A review. Mathematical and Computer Modelling 34, 55–80 (2001)
Vilain, M., Kautz, H.A.: Constraint propagation algorithms for temporal reasoning. In: AAAI 1986, pp. 132–144 (1986)
Allen, J.F.: Maintaining Knowledge about Temporal Intervals. Communication of ACM 26(11), 832–843 (1983)
HyTime Information Technology. Hypermedia / Time-based Structuring Language (HyTime), ISO/IEC 10743 (November 1992)
Moulin, B.: Conceptual graph approach for the representation of temporal information in discourse. Knowledge based systems 5(3), 183–192 (1992)
Li, H., Lavin, M.A.: Fast Hough Transform: A Hierarchical Approach. Journal on Graphical Models and Image Processing (CVGIP) (36), 139–161 (November/December 1986)
Freska, C.: Temporal Reasoning Based on Semi-intervals. Artificial Intelligence 54, 199–227 (1992)
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Ibrahim, Z.A.A., Ferrane, I., Joly, P. (2006). Temporal Relation Analysis in Audiovisual Documents for Complementary Descriptive Information. In: Detyniecki, M., Jose, J.M., Nürnberger, A., van Rijsbergen, C.J. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2005. Lecture Notes in Computer Science, vol 3877. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11670834_12
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DOI: https://doi.org/10.1007/11670834_12
Publisher Name: Springer, Berlin, Heidelberg
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