Cognitive Daily

ResearchBlogging.orgWhat makes something look glossy? At first, it doesn’t seem like a difficult question — it’s something smooth and reflective. But if you were to attempt to draw something that looked glossy, how would you to it? Now, the problem suddenly gets a lot more difficult. Taking a look at a photo of a glossy object might give you some clues. Here’s an example:

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I took this picture of my watch using the webcam on my computer. Notice that you can see the reflection of the computer screen in the bottom half of my watch face. You can’t see it on my face though — my face isn’t glossy. So one component of seeing an object as glossy is seeing a reflected image. You can also see highlights in glossy objects: notice that there are a couple bright spots on my glossy eyeglasses, even though the glasses are actually dark brown. There are more highlights in the metal surrounding my watch face. To draw a picture of a glossy object, you’d have to include these reflections and highlights.

But as early as 1850, researchers realized that there might be something more to how we see glossiness. Suppose you stand five feet away from a mirror and look at your reflection. All the depth cues would suggest that your reflection is ten feet away, not five feet away. One of the most important ways we judge distance, binocular disparity (the different perspectives we see on an object from each eye), would again put your reflection at ten feet away. There’s no way to incorporate binocular disparity into a normal drawing or photo. When an object is curved, like my glasses or watch case, the problem becomes even more complex — some reflections look closer, and others look farther away (like objects in your rear-view mirror). Does our visual system take all this into account when perceiving glossiness? Or does it simply look for highlights and reflections?

The advent of modern 3-D computer displays enabled Gunnar Wendt, Franz Faul, and Rainer Mausfeld to test this question.


They showed animated displays of objects to viewers using a stereoscopic display and systematically changed the “shininess” of the objects. Here’s an example of the type of image they used:

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The viewers rated each object for the glossiness and the realism of the display. Half the time, viewers saw the images with no binocular disparity, so that the image of the reflection appeared to be on the surface of the object. Half the time, each eye saw a different image, giving the appearance of highlights below or above the surface of the objects. Here are the results:

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Both the perceived glossiness of the objects and the perceived realism of the objects was significantly greater when highlights were realistically portrayed using a different image for each eye. This “highlight disparity,” the researchers say, is an important component of what makes objects appear glossy.

An interesting note — the second graph shows that at the highest values of shininess, perceived realism actually decreases. This might be because the computer display used couldn’t display a wide enough range of colors to appear realistic, or possibly because people don’t normally see objects as shiny as the ones depicted in the study.

This study also offers an interesting perspective on the debate about whether to buy a glossy or non-glossy display for your computer. While most people seem to prefer matte displays, in real-world use, because glossiness is enhanced due to binocular disparity, we may be able to accommodate to glossy displays relatively easily.

Wendt, G., Faul, F., & Mausfeld, R. (2008). Highlight disparity contributes to the authenticity and strength of perceived glossiness. Journal of Vision, 8(1), 1-10. DOI: 10.1167/8.1.14

Comments

  1. #1 Hao
    June 18, 2008

    Motoyoshi et. al. had a paper in Nature last year that suggested that glossiness might be computed easily through the skewness of the luminance histogram.

    http://www.nature.com/nature/journal/v447/n7141/full/nature05724.html

  2. #2 Chak
    July 3, 2008

    After looking at your photo, i have some questions in mind… How could you (or your brain) tell that, the white spot on your glasses is a reflection of light, but NOT a white physical spot in its design? And, before you tell me the watch surface is reflecting a computer screen, i didn’t know it, but my brain already know that the surface is reflecting… In fact, the things being reflected can be arbitary, from a clear object to just some blurry patterns. So how can the brain know it’s reflecting something?

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