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Fire Detection Algorithms Using Multimodal ... - Bilkent University

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BIBLIOGRAPHY 113[28] R. Fablet and P. Bouthemy. Motion recognition using nonparametric imagemotion models estimated from temporal and multiscale co-occurrencestatistics. IEEE Transactions on Pattern Analysis and Machine Intelligence,25:1619–1624, 2003.[29] S. Fazekas and D. Chetverikov. Analysis and performance evaluation of opticalflow features for dynamic texture recognition. Signal Processing:ImageCommunication, 22(7-8):680–691, 2007.[30] R. Fisher (Ed.). CVonline: The Evolving, Distributed, Non-Proprietary, On-Line Compendium of Computer Vision,http://homepages.inf.ed.ac.uk/rbf/cvonline/, Accessed at December2008.[31] G. L. Foresti, C. S. Regazzoni, and P. K. V. (Eds.). Multisensor SurveillanceSystems - The Fusion Perspective. Kluwer Academic Publishers, 2003.[32] D. Forsyth and J.Ponce. Computer Vision: A Modern Approach. PrenticeHall, 2002.[33] K. Fujita and S. Nayar. Recognition of dynamic textures using impulseresponses of state variables. In Proceedings of the Third International Workshopon Texture Analysis and Synthesis (Texture), pages 31–36, 2003.[34] O. N. Gerek and A. E. Cetin. Adaptive polyphase subband decompositionstructures for image compression. IEEE Transactions on Image Processing,9:1649–1659, October 2000.[35] A. Ghoreyshi and R. Vidal. Segmenting Dynamic Textures with Ising Descriptors,ARX Models and Level Sets. In Proceedings of the European Conferenceon Computer Vision / Dynamical Vision Workshop (ECCV/DV),2006.[36] P. Guillemant and J. Vicente. Real-time identification of smoke images byclustering motions on a fractal curve with a temporal embedding method.Optical Engineering, 40:554–563, 2001.[37] S. Haykin. Adaptive Filter Theory. Prentice Hall, 2002.

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