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Quantitative evaluation of perceived depth of transparently-visualized medical 3D data presented with a multi-view 3D display
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作者 Yuichi Sakano Yurina Kitaura +4 位作者 Kyoko Hasegawa Roberto Lopez-Gulliver Liang Li hiroshi ando Satoshi Tanaka 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2018年第3期115-130,共16页
Transparent visualization is used in many fields because it can visualize not only the frontal object but also other important objects behind it.Although in many situations,it would be very important for the 3D struct... Transparent visualization is used in many fields because it can visualize not only the frontal object but also other important objects behind it.Although in many situations,it would be very important for the 3D structures of the visualized transparent images to be perceived as they are simulated,little is known quantitatively as to how such transparent 3D structures are perceived.To address this question,in the present study,we conducted a psychophysical experiment in which the observers reported the perceived depth magnitude of a transparent object in medical images,presented with a multiview 3D display.For the visualization,we employed a stochastic point-based rendering(SPBR)method,which was developed recently as a technique for efficient transparentrendering.Perceived depth of the transparent object was smaller than the simulated depth.We found,however,that such depth underestimation can be alleviated to some extent by(1)applying luminance gradient inherent in the SPBR method,(2)employing high opacities,and(3)introducing binocular disparity and motion parallax produced by a multi-view 3D display. 展开更多
关键词 Transparent visualization automultiscopic 3D image psychophysics.
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