Abstract
In this paper, we present a study on the discrimination capabilities of colour, texture and shape MPEG-7 [1] visual descriptors, within the context of video sequences. The target is to facilitate the recognition of certain visual cues which would then allow the classification of natural disaster-related concepts. Low-level visual features are extracted using the MPEG-7 “eXperimentation Module” (XM) [2]. The extraction times associated to the levels of detail of the descriptors are measured. The pattern sets obtained as combination of significant levels of detail of different descriptors are the input to a Support Vector Machine (SVM), resulting on the classification accuracies. Preliminary results indicate that this approach could be useful for the implementation of real-time spatial regions classifiers.
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Manjunath, B.S., Salembier, P., Sikora, T.: Introduction to MPEG-7, 1st edn. John Wiley & Sons, Ltd., West Sussex, England
MPEG-7: Visual experimentation model (xm) version 10.0. ISO/IEC/JTC1/SC29/WG11, Doc. N4062 (2001)
Mikolajczyk, K., Schmid, C.: A performance Evaluation of Local Descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(10), 1615–1630 (2007)
Ojala, T., Aittola, M., Matinmikko, E.: Empirical Evaluation of MPEG-7 XM Color Descriptors in Content-Based Retrieval of Semantic Image Categories. In: ICPR 2002. 16th International Conference on Pattern Recognition, vol. 2, p. 21021 (2002)
Ojala, T., Mäenpää, T., Viertola, J., Kyllönen, J., Pietikäinen, M.: Empirical evaluation of MPEG-7 texture descriptors with a large-scale experiment. In: Proc. 2nd International Workshop on Texture Analysis and Synthesis, Copenhagen, Denmark, pp. 99–102 (2002)
Chang, C.-C., Lin, C.-J.: LIBSVM : a library for support vector machines (2001), software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
Russell, B.C., Torralba, A., Murphy, K.P., Freeman, W.T.: LabelMe: a database and web-based tool for image annotation, MIT AI Lab Memo AIM-2005-025 (September 2005)
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Molina, J., Spyrou, E., Sofou, N., Martínez, J.M. (2007). On the Selection of MPEG-7 Visual Descriptors and Their Level of Detail for Nature Disaster Video Sequences Classification. In: Falcidieno, B., Spagnuolo, M., Avrithis, Y., Kompatsiaris, I., Buitelaar, P. (eds) Semantic Multimedia. SAMT 2007. Lecture Notes in Computer Science, vol 4816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77051-0_6
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DOI: https://doi.org/10.1007/978-3-540-77051-0_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77033-6
Online ISBN: 978-3-540-77051-0
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