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Content archived on 2024-05-29

Perceptual analysis and measurement of surface texture


In this project, we aim to identify perceptual dimensions of surface texture and to find new computational features corresponding to these dimensions. By surface texture we mean the complex surface characteristics regarded as a combination of geometry (surface relief) and variation of reflectance function.

Computational features are statistical descriptors of surface textures. We believe that this problem can be characterised as follows:
1. Importance: Surface appearance is a critical characteristic of nearly all of today¿s commodity items. However, there are currently no accepted ways for producing perceptually meaningful measurements of surface texture, or even an agreement on what the principal perceptual dimensions are. Yet, this ability is key to producing intuitive and effective information systems that will be able to manage the explosion of this type of data that will soon take place due to recent advances in computer graphics and surface capture techniques.
2. Novelty: Psychometric studies into texture have so far been restricted to using single, still images of surface texture.

We believe that such data provide insufficient stimuli for observers and that they bias the computational features in often uncontrolled or unknown ways. We will use real time photorealistic rendering of BTF (Bidirectional Texture Functions) to provide observers with the rich stimuli they normally experience when examining surface textures and we will derive computational features that are intrinsic to surface directly from BTF. We are not aware of this approach having been reported in the literature before.

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