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Is the perception of 3D shape from shading based on assumed reflectance and illumination?

Todd JT, Egan EJ, Phillips F - Iperception (2014)

Bottom Line: A gauge figure adjustment task was used to measure observers' perceptions of local surface orientation on the depicted surfaces, and the probe points included 60 pairs of regions that both had the same orientation.The results show clearly that observers' perceptions of these three types of stimuli were remarkably similar, and that probe regions with similar apparent orientations could have large differences in image intensity.This latter finding is incompatible with any process for computing shape from shading that assumes any plausible reflectance function combined with any possible homogeneous illumination.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, The Ohio State University, Columbus, OH; e-mail: todd.44@osu.edu.

ABSTRACT
The research described in the present article was designed to compare three types of image shading: one generated with a Lambertian BRDF and homogeneous illumination such that image intensity was determined entirely by local surface orientation irrespective of position; one that was textured with a linear intensity gradient, such that image intensity was determined entirely by local surface position irrespective of orientation; and another that was generated with a Lambertian BRDF and inhomogeneous illumination such that image intensity was influenced by both position and orientation. A gauge figure adjustment task was used to measure observers' perceptions of local surface orientation on the depicted surfaces, and the probe points included 60 pairs of regions that both had the same orientation. The results show clearly that observers' perceptions of these three types of stimuli were remarkably similar, and that probe regions with similar apparent orientations could have large differences in image intensity. This latter finding is incompatible with any process for computing shape from shading that assumes any plausible reflectance function combined with any possible homogeneous illumination.

No MeSH data available.


Related in: MedlinePlus

Example images of different 3D shapes with different material properties and different inhomogeneous illuminations. The depicted materials include a translucent milky substance, hammered gold, glossy red paint, glass, four different types of cloth, and blue fur. The glass example was created by Toni Fresnedo (tonifresnedo.com) using the Maxwell renderer. The cloth examples are from Sadeghi et al. (2013) using a new state-of-the-art algorithm for simulating cloth materials. All of the cloth examples have the same depicted geometry and the same illumination, but they have different BRDFs, which produce noticeably different patterns of shading. All of the other examples were created using the VRAY renderer. The translucent material was created using a bidirectional surface scattering reflectance distribution function (BSSRDF) for skim milk based on measurements by Jensen, Marschner, Levoy, and Hanrahan (2001).
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Figure 10: Example images of different 3D shapes with different material properties and different inhomogeneous illuminations. The depicted materials include a translucent milky substance, hammered gold, glossy red paint, glass, four different types of cloth, and blue fur. The glass example was created by Toni Fresnedo (tonifresnedo.com) using the Maxwell renderer. The cloth examples are from Sadeghi et al. (2013) using a new state-of-the-art algorithm for simulating cloth materials. All of the cloth examples have the same depicted geometry and the same illumination, but they have different BRDFs, which produce noticeably different patterns of shading. All of the other examples were created using the VRAY renderer. The translucent material was created using a bidirectional surface scattering reflectance distribution function (BSSRDF) for skim milk based on measurements by Jensen, Marschner, Levoy, and Hanrahan (2001).

Mentions: The present results would not necessarily be incompatible with an assumed BRDF for the computation of 3D shape from shading if the assumption of homogeneous illumination were abandoned. That latter assumption is only adopted for computational convenience, and it is almost always violated in natural vision, especially in indoor environments. However, it is not at all clear how an assumed BRDF by itself would provide sufficient constraint to compute local surface orientation from inverse optics with patterns of illumination that are inhomogeneous. Moreover, it is also difficult to reconcile that assumption with the fact that human observers can identify a wide variety of material properties. For example, consider the images presented in Figure 10, which depict a translucent milky substance, hammered gold, glossy red paint, glass, four different types of cloth and blue fur. Not only can we identify the materials in these images, but we can also perceive the depicted 3D shapes, despite the fact that they all have different inhomogeneous patterns of illumination. These observations suggest that the perception of 3D shape and material properties are somehow determined simultaneously with one another, and that they do not depend on prior knowledge about the light field.


Is the perception of 3D shape from shading based on assumed reflectance and illumination?

Todd JT, Egan EJ, Phillips F - Iperception (2014)

Example images of different 3D shapes with different material properties and different inhomogeneous illuminations. The depicted materials include a translucent milky substance, hammered gold, glossy red paint, glass, four different types of cloth, and blue fur. The glass example was created by Toni Fresnedo (tonifresnedo.com) using the Maxwell renderer. The cloth examples are from Sadeghi et al. (2013) using a new state-of-the-art algorithm for simulating cloth materials. All of the cloth examples have the same depicted geometry and the same illumination, but they have different BRDFs, which produce noticeably different patterns of shading. All of the other examples were created using the VRAY renderer. The translucent material was created using a bidirectional surface scattering reflectance distribution function (BSSRDF) for skim milk based on measurements by Jensen, Marschner, Levoy, and Hanrahan (2001).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4441026&req=5

Figure 10: Example images of different 3D shapes with different material properties and different inhomogeneous illuminations. The depicted materials include a translucent milky substance, hammered gold, glossy red paint, glass, four different types of cloth, and blue fur. The glass example was created by Toni Fresnedo (tonifresnedo.com) using the Maxwell renderer. The cloth examples are from Sadeghi et al. (2013) using a new state-of-the-art algorithm for simulating cloth materials. All of the cloth examples have the same depicted geometry and the same illumination, but they have different BRDFs, which produce noticeably different patterns of shading. All of the other examples were created using the VRAY renderer. The translucent material was created using a bidirectional surface scattering reflectance distribution function (BSSRDF) for skim milk based on measurements by Jensen, Marschner, Levoy, and Hanrahan (2001).
Mentions: The present results would not necessarily be incompatible with an assumed BRDF for the computation of 3D shape from shading if the assumption of homogeneous illumination were abandoned. That latter assumption is only adopted for computational convenience, and it is almost always violated in natural vision, especially in indoor environments. However, it is not at all clear how an assumed BRDF by itself would provide sufficient constraint to compute local surface orientation from inverse optics with patterns of illumination that are inhomogeneous. Moreover, it is also difficult to reconcile that assumption with the fact that human observers can identify a wide variety of material properties. For example, consider the images presented in Figure 10, which depict a translucent milky substance, hammered gold, glossy red paint, glass, four different types of cloth and blue fur. Not only can we identify the materials in these images, but we can also perceive the depicted 3D shapes, despite the fact that they all have different inhomogeneous patterns of illumination. These observations suggest that the perception of 3D shape and material properties are somehow determined simultaneously with one another, and that they do not depend on prior knowledge about the light field.

Bottom Line: A gauge figure adjustment task was used to measure observers' perceptions of local surface orientation on the depicted surfaces, and the probe points included 60 pairs of regions that both had the same orientation.The results show clearly that observers' perceptions of these three types of stimuli were remarkably similar, and that probe regions with similar apparent orientations could have large differences in image intensity.This latter finding is incompatible with any process for computing shape from shading that assumes any plausible reflectance function combined with any possible homogeneous illumination.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, The Ohio State University, Columbus, OH; e-mail: todd.44@osu.edu.

ABSTRACT
The research described in the present article was designed to compare three types of image shading: one generated with a Lambertian BRDF and homogeneous illumination such that image intensity was determined entirely by local surface orientation irrespective of position; one that was textured with a linear intensity gradient, such that image intensity was determined entirely by local surface position irrespective of orientation; and another that was generated with a Lambertian BRDF and inhomogeneous illumination such that image intensity was influenced by both position and orientation. A gauge figure adjustment task was used to measure observers' perceptions of local surface orientation on the depicted surfaces, and the probe points included 60 pairs of regions that both had the same orientation. The results show clearly that observers' perceptions of these three types of stimuli were remarkably similar, and that probe regions with similar apparent orientations could have large differences in image intensity. This latter finding is incompatible with any process for computing shape from shading that assumes any plausible reflectance function combined with any possible homogeneous illumination.

No MeSH data available.


Related in: MedlinePlus