{"title":"Time-Derivative Estimation of Noisy Movie Data using Adaptive Control Theory","authors":"Soon-Hyun Park, Takami Matsuo","volume":20,"journal":"International Journal of Electrical and Information Engineering","pagesStart":2818,"pagesEnd":2826,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10414","abstract":"This paper presents an adaptive differentiator\r\nof sequential data based on the adaptive control theory. The\r\nalgorithm is applied to detect moving objects by estimating a\r\ntemporal gradient of sequential data at a specified pixel. We\r\nadopt two nonlinear intensity functions to reduce the influence\r\nof noises. The derivatives of the nonlinear intensity functions\r\nare estimated by an adaptive observer with \u03c3-modification\r\nupdate law.","references":"[1] Cucchiara,R., Grana,C., Piccardi,M., and Prati,A. : \"Detecting\r\nMoving Objects, Ghosts, and Shadows in Video Streams\", IEEE\r\nTrans. on PAMI, Vol.25, No.10, pp.1337-1342 (2003).\r\n[2] Cheung,S.-C. and Kamath,C. : \"Robust techniques for background\r\nsubtraction in urban traffic video\", Video Communications\r\nand Image Processing, SPIE Electronic Imaging, San Jose,\r\nJanuary (2004), UCRL-CONF-200706.\r\n[3] Manzanera,A. and Richefeu,J.C. : \"A robust and computationally\r\nefficient motion detection algorithm based on \u03a3 \u2212 \u0394 background estimation\", ICVGIP, Kolkata, India (2004).\r\nhttp:\/\/www.ensta.fr\/\u2566\u00a3manzaner\r\n[4] Halevy,G. and Weinshall,D. : \"Motion of disturbances: detection\r\nand tracking of multibody non-rigid motion\",Machine\r\nVision and Applications, Vol.11, pp.122-137 (1999).\r\n[5] Ibrir,S.: \"New differentiators for control and observation applications\",\r\nProc. of American Control Conference, pp.2522-2527\r\n(2001).\r\n[6] Ibrir,S.: \"Linear time-derivative trackers\", Automatica, Vol.40,\r\npp.397-405 (2004).\r\n[7] Wren,C., Azabayejani,A., Darrell,T. and Pentland,A.: \"Pfinder:\r\nReal-time tracking of the human body\", IEEE Trans. on PAMI,\r\nVol.19, No.7, pp.780-785 (1997).\r\n[8] Kuo,C.M., Hsieh,C.-H., Lin,H.-C., and Lu, P.-C.: \"Motion\r\nestimation algorithm with Kalman filter\", Electronics Letters,\r\nVol.30, No.15, pp.1204-1206 (1994).\r\n[9] Karmann,K.-P. and Brandt A.: \"Moving object recognition\r\nusing an adaptive background memory\", Time-Varying Image\r\nProcessing and Moving Object Recognition, V.Cappellini ed.,\r\n2, pp.289-307, Elsevier Sicence Publishers B.V. (1990).\r\n[10] K\u252c\u00bfoker,R., Cakar,,S., and O\u252c\u00bf z,C.: \"Moving object detection and\r\ntarget prediction in video image\", IJCI Proceedings of International\r\nConference on Signal Processing, Vol.1, No.2, pp.149-\r\n152 (2003).\r\n[11] Richefeu,J. and Manzanera,A. : \"A new hybrid differential\r\nfilter for motion detection\", ICCVG-04, Warsaw, Poland,\r\n22-24, Sept. (2004).\r\nhttp:\/\/www.ensta.fr\/\u2566\u00a3richefeu\/Publications\/\r\niccvg82.pdf\r\n[12] Narendra,K.S. and Annaswamy,A.M. : Stable Adaptive Systems,\r\nPrentice-Hall, Inc. (1989).\r\n[13] Ioannou,P.A. and Sun,J. : Robust Adaptive Control, Prentice-\r\nHall, Inc. (1996).\r\n[14] Marbled-Block (new version) marmor stat, Institut\r\nf\u252c\u00bfur Algorithmen und Kognitive Systeme (Group\r\nProf. Dr. H.-H. Nagel), Universit\u252c\u00bfat Karlsruhe,\r\nhttp:\/\/i21www.ira.uka.de\/image_sequences\/.\r\n[15] Shimai,H. , Kurita,T. , and Umeyama,S. : \"Adaptive Background\r\nEstimation by Robust Statistics\", IEICE Transaction,\r\nD-II, Vol.J86-D-II, No.6, pp.796-806 (2003) (in Japanese).\r\n[16] Shimai,H., Mishima,T., Kurita,T., and Umeyama,S. : \"Adaptive\r\nbackground estimation from image sequence by on-line Mestimation\r\nand its application to detection of moving objects\",\r\nProc. of Infotech Oulu Workshop on Real-Time Image Sequence\r\nAnalysis, pp.99-108 (2000).","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 20, 2008"}