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    Photogravure etchings at http://kamprint.com/ & http://kamprint.com/xpress/

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Mood Tags

Text-based searches for documents display thousands of results, most of them irrelevant unless you know exactly what you’re searching for. When searching for images, text-based searches are even less likely to hit the target. The problem is, the sort of remembered association that is best at recalling them works in fundamentally different ways for images and for words.

Naming the pictures lets computers search for them, but usually for objective data,  such as title, subject matter, place, medium, and so forth. This kind of search is helpful for finding illustrations to supplement verbal information. But pictures are far more than information. They evoke responses of excitement, reassurance, joy, dread, involvement, mystery — the whole panoply of human emotion. What if we could search by such responses?

I am currently engaged in setting up a system to do just that. But what about the beauty-in-the-eye-of- the-beholder problem, different people responding to the same picture in different ways? This is where you, the viewer, come in, if you like. The mood tags below link to graphic examples. What search terms would you use? Which mood tags would make sense to you in searching for images? What’s missing — what would you add?

Dynamic
Reflective
Mysterious
Sensual
Spontaneous
Expansive
Elegiac
Intimate
Luminous

Are these tags really right for the examples? There won’t be total agreement. But if certain tags consistently cluster around the same prints, then those tags will be useful in a search. What about prints with two or more moods, like a clearing sky after a storm? Such complexities make prints interesting and true-to-life. Let’s save multiple moods for later, assuming for the moment that one mood each is enough. Then we might look at textures (rough, soft, rhythmic, and so forth). The idea is to build viewers’ experiences into the design of the system used for searching images. Your responses are invited!

Printed from: http://www.kamprint.com/views/?p=144 .
© Peter Miller 2019.