Fire Detection Algorithms Using Multimodal ... - Bilkent University

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BIBLIOGRAPHY 111[8] CAVIAR: Context Aware Vision using Image-based Active Recognition.Test Case Scenarios - EC Funded CAVIAR project/IST 2001 37540,http://homepages.inf.ed.ac.uk/rbf/caviar/, Accessed at December2008.[9] A. Cetin, M. Akhan, B. Toreyin, and A.Aksay. Characterization of motionof moving objects in video. US Patent No. 20040223652, pending, 2004.[10] A. Cetin and R. Ansari. Signal recovery from wavelet transform maxima.IEEE Transactions on Signal Processing, 42:194–196, 1994.[11] A. Cetin and R. Ansari. Signal recovery from wavelet transform maxima.IEEE Transactions on Signal Processing, 42:194–196, 1994.[12] A. Cetin and D. Chetverikov. Dynamic Texture Detection inVideo Showcase, Multimedia Understanding through Semantics andLearning, EC Sponsored Network of Excellence, MUSCLE-NoE,http://www.muscle-noe.org/content/view/145/64/, Accessed atDecember 2008.[13] E. Cetin. Reconstruction of Signals from Fourier Transform Samples. SignalProcessing, 16:129–148, 1989.[14] D. Chamberlin and A. Rose. The flicker of luminous flames. In Proceedingsof the First International Symposium on Combustion. The CombustionInstitute, 1928.[15] A. Chan and N. Vasconcelos. Layered dynamic textures. In Proceedingsof the Conference on Neural Information Processing Systems (NIPS), pages203–210, December 2005.[16] A. Chan and N. Vasconcelos. Modeling, clustering, and segmenting videowith mixtures of dynamic textures. IEEE Transactions on Pattern Analysisand Machine Intelligence, 30(5):909–926, 2008.[17] T. Chen, P. Wu, and Y. Chiou. An early fire-detection method based onimage processing. In Proceedings of the IEEE International Conference onImage Processing (ICIP), pages 1707–1710, 2004.
BIBLIOGRAPHY 112[18] D. Chetverikov and R. Peteri. A brief survey of dynamic texture descriptionand recognition. In Proceedings of the Fourth International Conference onComputer Recognition Systems (CORES), pages 17–26, 2005.[19] R. Collins, A. Lipton, and T. Kanade. A system for video surveillance andmonitoring. In Proceedings of the 8-th International Topical Meeting onRobotics and Remote Systems. American Nuclear Society, April 1999.[20] P. L. Combettes. The foundations of set theoretic estimation. Proceedingsof the IEEE, 81(2):182–208, 1993.[21] J. Davis and A. Bobick. The representation and recognition of action usingtemporal templates. In Proceedings of the IEEE Conference on ComputerVision and Pattern Recognition (CVPR), pages 928–934, 1997.[22] J. M. de Dios, B. Arrue, A. Ollero, L. Merino, and F. Gomez-Rodriguez.Computer vision techniques for forest fire perception. Image and VisionComputing, 26(4), 2008.[23] Y. Dedeoglu, B. Töreyin, U. Gudukbay, and A. Cetin. Real-time fire andflame detection in video. In Proceedings of the IEEE International Conferenceon Acoustics, Speech and Signal Processing (ICASSP), pages 669–672,2005.[24] Y. Dedeoglu, B. Töreyin, U. Gudukbay, and A. Cetin. Multimodal Processingand Interaction: Audio, Video, and Text, chapter 6 - Surveillance Using BothVideo and Audio, pages 143–155. P. Maragos, A. Potamianos, P. Gros. (Eds.)Springer Science+Business Media, LLC, 2008.[25] H. Dreyfus. What Computers Can’t Do. 1972.[26] H. Dreyfus. What Computers Still Can’t Do: A Critique of Artificial Reason.MIT Press, 1992.[27] R. O. Duda, P. E. Hart, and D. G. Stork. Pattern Classification. Wiley-Interscience Publication, 2000.
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viiiçin de işaret işleme yöntem
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ixThis work was supported in part b
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LIST OF FIGURESxiv2.6 Three-state M
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LIST OF FIGURESxvi4.4 Two moving ob
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List of Tables1.1 Organization of t
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Chapter 1IntroductionDynamic textur
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CHAPTER 1. INTRODUCTION 3No fire de
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Chapter 2Flame Detection in Visible
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CHAPTER 2. FLAME DETECTION IN VISIB
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CHAPTER 3. FLAME DETECTION IN INFRA
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Chapter 4Short Range Smoke Detectio
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CHAPTER 4. SHORT RANGE SMOKE DETECT
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CHAPTER 4. SHORT RANGE SMOKE DETECT
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