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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

A perception correlated comparison method for dynamic meshes.

Libor Váša¹, Václav Skala

¹University of West Bohemia, Plzen, Czech Republic. lvasa@kiv.zcu.cz

IEEE Transactions on Visualization and Computer Graphics

|December 15, 2010

Summary

Researchers developed a new method to measure distortion in simplified 3D models. The Spatiotemporal Edge Difference (STED) metric better reflects how humans perceive changes in animated meshes compared to older methods.

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Area of Science:

Computer Graphics
Geometric Modeling
Digital Signal Processing

Background:

Triangular meshes are widely used in computer graphics for representing 3D shapes.
Mesh simplification and compression aim to reduce data size while preserving visual fidelity.
Existing methods for evaluating distortion in simplified meshes, such as mean squared error, have limitations.

Purpose of the Study:

To identify drawbacks in current distortion evaluation methods for simplified 3D meshes.
To propose a new, more accurate metric for assessing mesh distortion.
To validate the proposed metric against subjective human perception.

Main Methods:

Conducted subjective testing to gather human opinions on mesh distortion.
Analyzed the limitations of existing error measures like mean squared error.
Developed and implemented a novel distortion metric called Spatiotemporal Edge Difference (STED).

Main Results:

Existing error measures show significant drawbacks in accurately reflecting perceived distortion.
Subjective testing provided valuable insights into human perception of mesh deformation.
The new Spatiotemporal Edge Difference (STED) metric demonstrated a superior correlation with subjective evaluations.

Conclusions:

Current objective measures for mesh distortion are inadequate for dynamic surfaces.
The Spatiotemporal Edge Difference (STED) metric offers a more reliable way to evaluate distortion in animated 3D models.
STED can aid in developing better mesh compression and simplification algorithms.