Material sound source localization through headphones

[EN] In the present paper a study of sound localization is carried out, considering two different sounds emitted from different hit materials (wood and bongo) as well as a Delta sound. The motivation of this research is to study how humans localize sounds coming from different materials, with the purpose of a future implementation of the acoustic sounds with better localization features in navigation aid systems or training audio-games suited for blind people. Wood and bongo sounds are recorded after hitting two objects made of these materials. Afterwards, they are analysed and processed. On the other hand, the Delta sound (click) is generated by using the Adobe Audition software, considering a frequency of 44.1 kHz. All sounds are analysed and convolved with previously measured non-individual Head-Related Transfer Functions both for an anechoic environment and for an environment with reverberation. The First Choice method is used in this experiment. Subjects are asked to localize the source position of the sound listened through the headphones, by using a graphic user interface. The analyses of the recorded data reveal that no significant differences are obtained either when considering the nature of the sounds (wood, bongo, Delta) or their environmental context (with or without reverberation). The localization accuracies for the anechoic sounds are: wood 90.19%, bongo 92.96% and Delta sound 89.59%, whereas for the sounds with reverberation the results are: wood 90.59%, bongo 92.63% and Delta sound 90.91%. According to these data, we can conclude that even when considering the reverberation effect, the localization accuracy does not sig- nificantly increase. © Pleiades Publishing, Ltd., 2012.This research was supported by Research Center in Graphic Technology from the Universidad Politecnica de Valencia.Dunai, L.; Peris Fajarnes, G.; Lengua, I.; Tortajada Montañana, I. (2012). Material sound source localization through headphones. Acoustical Physics. 58(5):610-617. doi:10.1134/S1063771012050077S610617585D. S. Brungart and W. M. Rabinowitz, J. Acoust. Soc. Am. 106, 1465 (1999).D. S. Brungart, I. Nathaniel, and W. R. Rabinowitz, J. Acoust. Soc. Am. 106, 1956 (1999).H. Bruce and D. Hirsh, J. Acoust. Soc. Am. 31, 486 (1959).D. I. Shore, S. E. Hall, and R. M. Klein, J. Acoust. Soc. Am. 103, 3730 (1998).J. C. Kidd and J. H. Hogloben, J. Acoust. Soc. Am., 116, 1116 (2004).L. Dunai, G. P. Fajarnes, B. D. Garcia, N. O. Araque, and F. B. Simon, Acoust. Phys. 55, 448 (2009).L. Dunai, G. P. Fajarnes, B. D. Garcia, and V. S. Praderas, Acoust. Phys. 56, 348 (2010).M. Gröhn, Proc. Int. Conf. on Auditory Display, Kyoto, 2002.E. S. Malinina and I. G. Andreeva, Acoust. Phys. 56, 576 (2010).E. D. Shabalina, N. V. Shirgina, and A. V. Shanin, Acoust. Phys. 56, 525 (2010).A. Pompey, M. A. Sumbatyan, and N. F. Todorov, Acoust. Phys. 55, 760 (2009).R. L. Klatzky, D. K. Pai, and E. P. Krotkov, Presence: Teleoperators and Virtual Environments 9, 399 (2000).M. Aramaki, M. Besson, R. Kronland-Martinet, and S. Ystad, Proc. 5th Int. Symp. on Comp. Music Model. Retriev. (CMMR 2008), Copenhagen, 2008, pp. 1–8.W. Gaver, PhD Dissertation, Univ. California, San Diego, 1988.N. I. Durlach, A. Rigapolus, X. D. Pang, W. S. Woods, A. Kulkarni, H. S. Colburn, and E. M. Wenzel, Presence: Teleoperators and Virtual Environments 1, 251 (1992).S. A. Gelfand, Essentials of Audiology, 3rd ed. (Thieme Medical Publishers, New York, 2009).J. Jerger, ASHA 4, 139 (1962).H. Mershon, W. L. Ballenger, A. D. Little, P. L. McMurtry, and J. L. Buchanan, Perception 18, 403 (1989).D. O. Kim, A. Moiseff, T. J. Bradley, and J. Gull, Acta Otolaryngologica 128, 328 (2008).P. Zahorik, Proc. Int. Conf. on Auditory Display, Kyoto, 2002

Parametric effects on the evaluation of threshold chromaticity differences using red printed samples

This paper was published in JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: https://doi.org/10.1364/JOSAA.36.000510. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.[EN] Results from different authors showed deviations of radial orientation in the a*-b* plane (tilt) for the major axes of chromaticity-discrimination ellipses centered around the International Commission on Illumination (CIE) red color center [Color Res. Appl. 3, 149 (1978)], which are not considered by most of the current advanced color-difference formulas (e.g., CIEDE2000). We performed a visual experiment using red printed samples in order to test the influence of the separation between samples (gap) on the mentioned tilt. Our results confirm a counterclockwise tilt of fitted a*-b* ellipses with a magnitude of approximately 36 degrees for samples with no separation, which is similar to that detected by other authors, and a reduction of the mentioned tilt owing to the separation of the samples. We detected a tilt of approximately 22 degrees for samples with a black gap of 0.5 mm and a tilt of approximately 25 degrees for samples with a white gap of 3 mm. Notably, the uncertainty of previous values given by the corresponding credibility intervals of 95% posterior probability is approximately +/- 8 degrees of the mean values. Finally, we study the performance of the most widely used color-difference formulas in the graphic arts sector using our current experimental results, and conclude that the performance of the CAM02-SCD and CAM02-UCS color-difference formulas is significantly better than that of the CIEDE2000 formula.Brusola Simón, F.; Tortajada Montañana, I.; Jorda-Albiñana, B.; Melgosa, M. (2019). Parametric effects on the evaluation of threshold chromaticity differences using red printed samples. Journal of the Optical Society of America A. 36(4):510-517. https://doi.org/10.1364/JOSAA.36.000510S510517364Melgosa, M. (2007). Request for existing experimental datasets on color differences. Color Research & Application, 32(2), 159-159. doi:10.1002/col.20300Luo, M. R., Cui, G., & Rigg, B. (2001). The development of the CIE 2000 colour-difference formula: CIEDE2000. Color Research & Application, 26(5), 340-350. doi:10.1002/col.1049Luo, M. R., & Rigg, B. (1986). Chromaticity-discrimination ellipses for surface colours. Color Research & Application, 11(1), 25-42. doi:10.1002/col.5080110107Alman, D. H., Berns, R. S., Snyder, G. D., & Larsen, W. A. (1989). Performance testing of color-difference metrics using a color tolerance dataset. Color Research & Application, 14(3), 139-151. doi:10.1002/col.5080140308Berns, R. S., Alman, D. H., Reniff, L., Snyder, G. D., & Balonon-Rosen, M. R. (1991). Visual determination of suprathreshold color-difference tolerances using probit analysis. Color Research & Application, 16(5), 297-316. doi:10.1002/col.5080160505Witt, K. (1999). Geometric relations between scales of small colour differences. Color Research & Application, 24(2), 78-92. doi:10.1002/(sici)1520-6378(199904)24:23.0.co;2-mMelgosa, M., Hita, E., Poza, A. J., Alman, D. H., & Berns, R. S. (1997). Suprathreshold color-difference ellipsoids for surface colors. Color Research & Application, 22(3), 148-155. doi:10.1002/(sici)1520-6378(199706)22:33.0.co;2-rIndow, T., Robertson, A. R., Von Grunau, M., & Fielder, G. H. (1992). Discrimination ellipsoids of aperture and simulated surface colors by Matching and paired comparison. Color Research & Application, 17(1), 6-23. doi:10.1002/col.5080170106Xu, H., & Yaguchi, H. (2005). Visual evaluation at scale of threshold to suprathreshold color difference. Color Research & Application, 30(3), 198-208. doi:10.1002/col.20106Huang, M., Liu, H., Cui, G., Luo, M. R., & Melgosa, M. (2012). Evaluation of threshold color differences using printed samples. Journal of the Optical Society of America A, 29(6), 883. doi:10.1364/josaa.29.000883Wen, S. (2012). A color difference metric based on the chromaticity discrimination ellipses. Optics Express, 20(24), 26441. doi:10.1364/oe.20.026441Huang, M., Liu, H., Cui, G., & Luo, M. R. (2011). Testing uniform colour spaces and colour-difference formulae using printed samples. Color Research & Application, 37(5), 326-335. doi:10.1002/col.20689Rich, R. M., Billmeyer, F. W., & Howe, W. G. (1975). Method for deriving color-difference-perceptibility ellipses for surface-color samples. Journal of the Optical Society of America, 65(8), 956. doi:10.1364/josa.65.000956MacAdam, D. L. (1942). Visual Sensitivities to Color Differences in Daylight*. Journal of the Optical Society of America, 32(5), 247. doi:10.1364/josa.32.000247Witt, K. (1995). Cie guidelines for coordinated future work on industrial colour-difference evaluation. Color Research & Application, 20(6), 399-403. doi:10.1002/col.5080200609García, P. A., Huertas, R., Melgosa, M., & Cui, G. (2007). Measurement of the relationship between perceived and computed color differences. Journal of the Optical Society of America A, 24(7), 1823. doi:10.1364/josaa.24.001823Guan, S.-S., & Luo, M. R. (1999). Investigation of parametric effects using small colour differences. Color Research & Application, 24(5), 331-343. doi:10.1002/(sici)1520-6378(199910)24:53.0.co;2-9Montag, E. D., & Wilber, D. C. (2002). A comparison of constant stimuli and gray-scale methods of color difference scaling. Color Research & Application, 28(1), 36-44. doi:10.1002/col.10112Strocka, D., Brockes, A., & Paffhausen, W. (1983). Influence of experimental parameters on the evaluation of color-difference ellipsoids. Color Research & Application, 8(3), 169-175. doi:10.1002/col.5080080308Witt, K. (1990). Parametric effects on surface color-difference evaluation at threshold. Color Research & Application, 15(4), 189-199. doi:10.1002/col.5080150404Xin, J. H., Lam, C. C., & Luo, M. R. (2001). Investigation of parametric effects using medium colour-difference pairs. Color Research & Application, 26(5), 376-383. doi:10.1002/col.1053Cui, G., Luo, M. R., Rigg, B., & Li, W. (2001). Colour-difference evaluation using CRT colours. Part II: Parametric effects. Color Research & Application, 26(5), 403-412. doi:10.1002/col.1056Berns, R. S. (1996). Deriving instrumental tolerances from pass-fail and colorimetric data. Color Research & Application, 21(6), 459-472. doi:10.1002/(sici)1520-6378(199612)21:63.0.co;2-vBrusola, F., Tortajada, I., Lengua, I., Jordá, B., & Peris, G. (2015). Bayesian approach to color-difference models based on threshold and constant-stimuli methods. Optics Express, 23(12), 15290. doi:10.1364/oe.23.015290Saeedi, H., & Gorji Kandi, S. (2018). How anisotropy of CIELAB color space affects the separation effect: an experimental study. Journal of the Optical Society of America A, 36(1), 51. doi:10.1364/josaa.36.000051Yebra, A., Huertas, R., Pérez, M. M., & Melgosa, M. (2002). On the relationship between tilt ofa*b* tolerance ellipses in blue region and tritanopic confusion lines. Color Research & Application, 27(3), 180-184. doi:10.1002/col.1005

Effect of the chromatic assimilation (Bezold effect) in the vision of the content on a dinner plate

The color perception on a dinner plate depends on the color and distribution of the surrounding content. It is unthinkable to eat a typical Spanish dish, paella blue, or drink red or green milk. The color is also an indicator of expiration. The color of food intake predisposes us, which is known as the phrase “eat with our eyes” while we see an appetizing menu. Besides, the importance of the composition of a dish, distribution and presentation is critical in their perception. We are working long time in the lab of The Engineering Design Faculty on the perception of the distribution of objects, especially on the Bezold effect. It is interesting to apply the results of the perception that people have of the distribution of food, anchovies, olives, potatoes, etc. on a plate. To carry out this work we have used people who show the human reaction to the various situations described. Most relevant results, we note that the background (e.g. dish, decoration) with a horizontal grating, the effect of chromatic assimilation is greater than the vertical orientation, regardless of the orientation of the sequence.Tortajada Montañana, I.; Montalvá Colomer, J.; Aguilar Rico, M. (2011). Effect of the chromatic assimilation (Bezold effect) in the vision of the content on a dinner plate. Journal of Life Sciences. 5(9):772-775. doi:10.17265/1934-7391/2011.09.015S7727755

Parametric effects by using the strip-pair comparison method around red CIE color center

[EN] The strip comparison method, based on the serial exploration method described by Torgerson [Theory and Methods of Scaling; Wiley & Sons (1958); Chap. 7], for the development of near-threshold color difference models was presented and validated with theoretical data by the authors in a previous work. In this study, we investigate parametric effects derived from the use of the strip comparison method on chromaticity-discrimination ellipses around the red CIE color center. The results obtained led to the conclusion that the strip comparison method has little effect on the parameters of the chromaticity-discrimination ellipses determined by the pair comparison method when pairs of patches in the strips are separated by a black line 0.5 mm thick or are separated by 3 mm spacing on a white background and also correlates well with the parameters reported by other authors using the pair comparison method at the threshold.Brusola Simón, F.; Tortajada Montañana, I.; Lengua, I.; Jorda-Albiñana, B.; Peris Fajarnes, G. (2020). Parametric effects by using the strip-pair comparison method around red CIE color center. Optics Express. 28(14):19966-19977. https://doi.org/10.1364/OE.395291S1996619977281

Strip-pair comparison method for building threshold color-difference model: theoretical model validation

[EN] This paper presents a method for developing color-difference models near a threshold, based on the serial exploration method described by Torgerson [Theory and Methods of Scaling; Wiley & Sons (1958); Chap. 7], involving the construction of color-control strips of patches arranged in arrays of 2 x n, where n is the number of pairs in the strip. The patches in the lower row should be calorimetrically identical, while the color of the patches in the upper row should vary progressively in constant steps of CIELAB color difference along selected color space vector directions. Prospective observers are instructed to indicate the patch pair number for which they begin to perceive a slight color difference between corresponding patches. The frequency data obtained from the observers was used to build a threshold color-difference model. The intention was to validate the method with theoretical data to determine the effect of the precision with which the strips are constructed, on the accuracy of the estimated parameters. Theoretical frequency data was generated using the CIE94 color difference formula, whose associated color discrimination ellipsoid parameters are very easy to determine, associated with a hypothetical logistic psychometric curve for different color centers. The proposed method allows to determine color discrimination parameters with a precision nearby 4% and an accuracy of 3% with respect to the simulated theoretical parameters, for color samples generated with a standard deviation of Delta E*(ab)=0.2 of the superimposed error around the ideal color difference of pairs of patches.Brusola Simón, F.; Tortajada Montañana, I.; Lengua, I.; Jorda-Albiñana, B.; Peris Fajarnes, G. (2020). Strip-pair comparison method for building threshold color-difference model: theoretical model validation. Optics Express. 28(14):21336-21347. https://doi.org/10.1364/OE.395256S2133621347281

Evaluación del efecto Bezold mediante el diseño de una aplicación de escritorio interactiva

[ES] A finales del siglo XIX Bezold describió un fenómeno descubierto por Chevreul denominado contraste inverso, efecto expansión o efecto Bezold. Recientemente, Tortajada, Montalvá y Aguilarlo han cuantificado usando redes de Ronchi representadas sobre papel. En este trabajo se presenta una aplicación de escritorio interactiva que permite medir rápida y eficientemente la aportación de un observador que evalúa el efecto Bezold en patrones de franjas de color, giro y ángulo de observación variables.La interfaz de la nueva aplicación tiene dos círculos blancos idénticos sobre un fondo neutro. En el interior de los mismos aparecen las muestras a comparar, ambas con iguales valores cromáticospero en una se produce efecto Bezold (provocado por redes de Ronchi) y en la otra no (provocado por un círculo concéntrico macizo), de forma que el observador debe intentar igualarlas. Como resultado obtenemos, para cada muestra presentada, los valores de Lque se han variado para realizar la igualación, lo cual nos indica el valor del efecto Bezold para esa muestra.[EN] At the end of XIX century Bezold described a Chevreul discovered effect named inverse contrast, expansion effect or Bezold effect. Recently, Tortajada, Montalvá and Aguilar have quantified it using Ronchi patterns represented on paper. In this work an interactive desktop application, which leads to a fast and efficient observer input measurement over Bezold variable color, spin and angle stripes, is presented. The new application' s interface has two identical white circles on a neutral background. The samples to be compared appear inside them, both with the same chromatic values but in one there is a Bezold effect (due to Ronchi's grating) and in the other there is not (due to a so lid concentric circle), so the observer will try to match each other. As a result we get, for each pair, the variation of L carried out to compensate the effect, and this variation is used to indicate the value of the Bezold effect for that sample.Tortajada Montañana, I.; J.V. Del_Valle; Lengua, I.; Brusola Simón, F. (2019). Bezold effect evaluation through the design of an interactive desktop application. OPTICA PURA Y APLICADA. 52(2):1-8. https://doi.org/10.7149/OPA.52.2.51008S1852

Utilización de filtros gaussianos para la predicción del efecto Bezold en muestras de color dispuestas sobre redes de Ronchi

Hasta la fecha no se ha desarrollado un modelo definitivo que permita predecir con fiabilidad la sensación de color que se produce al observar estímulos de color dispuestos sobre determinados tipos de patrones compuestos por tramas de inducción sobre fondos en color o redes de Ronchi. En este trabajo se presenta un método basado en la utilización de filtros gaussianos que permite, de manera aproximada, predecir la variación de sensación de color que se produciría sobre una muestra al ser observada cuando se dispone sobre alguno de los patrones citados. La aproximación es de carácter visual/cualitativo y supone un paso más hacia el desarrollo de un modelo cuantitativo para la predicción del fenómeno

Bayesian approach for developing threshold color-difference models by the strip-pair comparison method

[EN] A Bayesian approach alternative to the one used in the strip-pair comparison method for developing threshold color-difference models is presented in this paper. Strip-pair comparison method is based on the construction of color-control strips made of pairs of patches put in contact and ordered by increasing the CIELAB color difference. Observers are required to indicate the number of the pair of patches in every strip for which they begin to perceive a just noticeable color difference. Frequency data obtained, from repeating several times the visual assessment, is recorded to build a Bayesian multinomial logistic regression model, which allows the determination of the coefficients of the color discrimination ellipsoids. The results of the Bayesian approach agree closely with the results obtained to validate strip-pair comparison method for the same theoretical frequency data. The main advantage of the Bayesian approach over many other methods is that it allows a direct analysis of the statistical variability of the estimated parameters by means of confidence intervals and other measures of statistical variability.Brusola Simón, F.; Tortajada Montañana, I.; Jorda-Albiñana, B.; Gonzalez-Del-Rio, J.; Lengua, I. (2021). Bayesian approach for developing threshold color-difference models by the strip-pair comparison method. Optics Express. 29(17):26553-26568. https://doi.org/10.1364/OE.432157S2655326568291

New educative methods in the usage of audiovisual content in mobiles

[EN] The paper proposes new paradigms in education regarding usage of audiovisual contents adapted to mobile devices, under the perspective of changes in the conventional learning process through the web from student side. The knowledge of the educational design processes by professors, a concept known as m-learning, will allow to demonstrate the advantages and disadvantages under the student¿s perspective. These constraints are focused, firstly on adapting contents and, more specifically, on the real technical implementation of audiovisual contents and the mechanism and interaction processes. On the other hand, it is important to emphasize advances in new digital formats relating to the new generation mobile phones, which allow to integrate contents in the learning process, ubiquitous learning. Finally, considerations and conclusions addressed to the educators who would like to adapt traditional contents to the new tools and formats will be established.Magal Royo, T.; Tortajada Montañana, I.; Giménez López, JL.; Giménez Alcalde, F. (2010). New educative methods in the usage of audiovisual content in mobiles. Procedia Social and Behavioral Sciencies. 2(2):4492-4496. doi:10.1016/j.sbspro.2010.03.718S449244962

SISTEMAS DE REPRESENTACIÓN: Sistema diédrico

En este objeto de aprendizaje se muestran contenidos básicos que los alumnos que llegan a la universidad deberían tener sobre la asignatura de formación básica de "Expresión Gráfica" referentes a los sistemas de representación y más en concreto referentes al sistema diédrico.https://polimedia.upv.es/visor/?id=b9891750-5cdc-11e8-aab9-a1a4e108f2abTortajada Montañana, I. (2018). SISTEMAS DE REPRESENTACIÓN: Sistema diédrico. http://hdl.handle.net/10251/105679DE