997 resultados para color cycle
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\0\05{\0\0\0\0\0\0\0\0 a uniform wall illuminated by a spot light often gives a strong impression of the illuminant color. How can it be possible to know if it is a white wall illuminated by yellow light or a yellow wall illuminated by white light? If the wall is a Lambertian reflector, it would not be possible to tell the difference. However, in the real world, some amount of specular reflection is almost always present. In this memo, it is shown that the computation is possible in most practical cases.
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Urquhart, C., Spink, S., Thomas, R., Yeoman, A., Durbin, J., Turner, J., Fenton, R. & Armstrong, C. (2004). JUSTEIS: JISC Usage Surveys: Trends in Electronic Information Services Final report 2003/2004 Cycle Five. Aberystwyth: Department of Information Studies, University of Wales Aberystwyth. Sponsorship: JISC
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Urquhart, C. (editor for JUSTEIS team), Spink, S., Thomas, R., Yeoman, A., Durbin, J., Turner, J., Armstrong, A., Lonsdale, R. & Fenton, R. (2003). JUSTEIS (JISC Usage Surveys: Trends in Electronic Information Services) Strand A: survey of end users of all electronic information services (HE and FE), with Action research report. Final report 2002/2003 Cycle Four. Aberystwyth: Department of Information Studies, University of Wales Aberystwyth with Information Automation Ltd (CIQM). Sponsorship: JISC
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IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1338-1343, 2003.
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Thatcher, Rhys, et al., 'Influence of blood donation on O-2 uptake on-kinetics, peak O-2 uptake and time to exhaustion during severe-intensity cycle exercise in humans', Experimental Physiology (2006) 91(3) pp.499-509 RAE2008
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26 hojas : fotografías a color.
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47 hojas : ilustraciones, fotografías a color, muestras.
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13 hojas.
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19 hojas : ilustraciones, fotografías a color
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11 hojas : ilustraciones, fotografías a color.
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27 hojas : ilustraciones, fotografías
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A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation, and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24% is observed in 17 out of 21 test sequences. In all but one case the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.