Visualising movement in museums and on stage

A couple of roughly related projects, both looking at how people move around in cultural contexts.

The first one looks at how museum visitors find their way through collections. Andrew Oriani is a physicist and apparently knows a thing or two about statistical mechanics. While taking an art class:

Andrew sat for about 20 minutes apiece in three galleries of the Cleveland Museum of Art, and as visitors entered he tracked their route and made notations of where they stopped and for how many seconds. A line indicates a path of movement. A dot indicates when someone stopped to look. The dots are accompanied by little notations indicating how many seconds the viewer stood still.

What he found was that people didn’t tend to linger very long in front of objects and that they didn’t move through galleries in a particularly linear way. Take a look at the drawings he made. I daresay someone from the world of retail psychology would have some interesting thoughts to add to all of this.

The comments are well worth a flick through. Apparently there’s been a fair amount of work in this area and people were keen to flag up prior research, the Vistor Studies Association and some early-stage work from a European museums research project that’s “looking at ways of using head-mounted cameras to look at walkthroughs as an analysis, documentation and (perhaps in some ways) design tool”. Here’s a video of what they’re doing:

I found that original post via, which I’d recommend you subscribe to.

The second thing I wanted to point to is Tom Armitage‘s commission for myShakespeare:

Spirits Melted Into Air takes individual scenes or speeches – in this case, from the 2012 Royal Shakespeare Company productions of Richard III andThe Comedy of Errors – and produces data-visualisations of actors’ motion during them.

I thought this was the most satisfying of the recent myShakespeare commissions, although I can’t say I went a bundle on the visualisation aspects. It was apparently only a short exploration and Tom’s pointed to some other directions this sort of thing could go that sound good.

Tracking actors across performances sounds like it could be the most interesting of these. Extending this to compare different actors or the same actors in different productions, would also be fascinating (if improbable). Do some actors tend to be more animated than others? Which are the more static roles? Do some venues/audiences tend to have a dampening affect on a production?

As Tom says, automating the data capture would help and again, other sectors have interesting prior art in this area. SportVU are tracking player movement in basketball games using overhead cameras. Adidas’s miCoach system uses sensors for similar but different data (and would be much cheaper to transfer across). Actually, looking back at my previous paragraph I think I’m far too used to the embarrassment of riches available to sports data analysts.

There’s a video for this project too:

Published by Chris Unitt

I work at One Further, doing digital projects with cultural organisations. Follow @ChrisUnitt or find me on LinkedIn.