Abstract
Recently, research for the summarization of video data has been studied a lot due to the proliferation of user created contents. Besides, the use of multiple cameras for the collection of the video data has been increasing, but most of them have used the multi-camera system either to cover the wide area or to track moving objects. This paper focuses on getting diverse views for a single event using multi-camera system and deals with the problem of summarizing event sequences collected in the office environment based on this perspective. Summarization includes camera view selection and event sequence summarization. View selection makes a single event sequence from multiple event sequences as selecting optimal views in each time, for which domain ontology based on the elements in an office environment and rules from questionnaire surveys have been used. Summarization generates a summarized sequence from a whole sequence, and the fuzzy rule-based system is used to approximate human decision making. The degrees of interests input by users are used in both parts. Finally, we have confirmed that the proposed method yields acceptable results using experiments of summarization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhu, X., et al.: Hierarchical video content description and summarization using unified semantic and visual similarity. Multimedia Systems 9(1), 31–53 (2003)
Li, Y., et al.: Techniques for movie content analysis and skimming. IEEE Signal Processing Magazine 23(2), 79–89 (2006)
Tseng, B.L., et al.: Using MPEG-7 and MPEG-21 for personalizing video. IEEE Multimedia 11(1), 42–53 (2004)
Petkovic, M., Jonker, W.: An overview of data models and query languages for content-based video retrieval. In: Int. Conf. on Advances in Infrastructure for E-Business, Science, and Education on the Internet. l‘Aquila, Italy (2000)
Silva, G.C., et al.: Evaluation of video summarization for a large number of cameras in ubiquitous home. In: Proc. of the 13th ACM Int. Conf. on Multimedia, pp. 820–828 (2005)
Farwer, Sumi, Y., Mase, K., et al.: Collaborative capturing and interpretation of interactions. In: Pervasive 2004 Workshop on Memory and Sharing of Experiences, pp. 1–7 (2004)
Zhang, C.C., et al.: MyView: Personalized event retrieval and video compositing from multi-camera video images. In: Smith, M.J., Salvendy, G. (eds.) HCII 2007. LNCS, vol. 4557, pp. 549–558. Springer, Heidelberg (2007)
Dorado, A., et al.: A rule-based video annotation system. IEEE Trans. on Circuits and Systems for Video Technology 14(5), 622–633 (2004)
Black, J., Ellis, T.: Multi-camera image tracking. Image and Vision Computing 24, 1256–1267 (2006)
Porikli, F.M., Divakaran, A.: Multi-camera calibration, object tracking, and query generation. In: IEEE Int. Conf. on Multimedia and Expo, vol. 1, pp. 653–656 (2003)
Fogarty, J., et al.: Predicting human interruptibility with sensors. ACM Trans. on Computer-Human Interaction 12(1), 119–146 (2005)
Oliver, N., et al.: Layered representations for learning and inferring office activity from multiple sensory channels. Computer Vision and Image Understanding 96(2), 163–180 (2004)
Horrocks, I., Patel-Schneider, P.F.: A proposal for an OWL rules language. In: Proc. of the 13th Int. World Wide Web Conf., pp. 723–731 (2004)
Lertworasirikul, S., et al.: Fuzzy data envelopment analysis (DEA): A possibility approach. Fuzzy Sets & Systems 139(2), 3–29 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Park, HS., Cho, SB. (2008). A Fuzzy Rule-Based System with Ontology for Summarization of Multi-camera Event Sequences. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_81
Download citation
DOI: https://doi.org/10.1007/978-3-540-69731-2_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
Online ISBN: 978-3-540-69731-2
eBook Packages: Computer ScienceComputer Science (R0)