Evaluation of shape recovery algorithm for translucent objects

The human visual system can estimate the three-dimensional shapes of translucent objects. However, the shape estimation of translucent objects is less accurate than that of opaque objects. The specular component is particularly important in the shape perception of translucent objects because it is robust, whereas the non-specular component is affected by translucency. Previously, we developed a shape recovery algorithm as a computational model of human shape perception from opaque specular images. The algorithm primarily uses the specular component and secondarily uses the non-specular component. In the current study, the shape recovery performance of this algorithm for translucent objects was evaluated against ground-truth shapes. The results showed that the reconstruction of the three-dimensional shapes of low-translucency objects by the algorithm was comparable to that of opaque specular images. A modification of the algorithm involving the reversal of the non-specular component was effective for high-translucency objects. However, even with this modification, the estimation accuracy for high-translucency objects was lower than that for opaque objects. These results provide new insight into the possible mechanisms of shape perception for translucent objects.

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Publication Details

Journal
Scientific Reports
Published
2026-05-02
DOI
https://doi.org/10.1038/s41598-026-50949-6
Primary Topic
Medical Image Segmentation Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation of shape recovery algorithm for translucent objects

Takeaki Shimokawa
Scientific Reports
Medical Image Segmentation Techniques
article

Evaluation of shape recovery algorithm for translucent objects

Takeaki Shimokawa
article en

Abstract

The human visual system can estimate the three-dimensional shapes of translucent objects. However, the shape estimation of translucent objects is less accurate than that of opaque objects. The specular component is particularly important in the shape perception of translucent objects because it is robust, whereas the non-specular component is affected by translucency. Previously, we developed a shape recovery algorithm as a computational model of human shape perception from opaque specular images. The algorithm primarily uses the specular component and secondarily uses the non-specular component. In the current study, the shape recovery performance of this algorithm for translucent objects was evaluated against ground-truth shapes. The results showed that the reconstruction of the three-dimensional shapes of low-translucency objects by the algorithm was comparable to that of opaque specular images. A modification of the algorithm involving the reversal of the non-specular component was effective for high-translucency objects. However, even with this modification, the estimation accuracy for high-translucency objects was lower than that for opaque objects. These results provide new insight into the possible mechanisms of shape perception for translucent objects.

Scientific Reports
Hiroshima City University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 9%
Medical Image Segmentation Techniques
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