Solstice Cyclists part 1: data capture

The Solstice Cyclists, an intentionally-disorganized group of mostly-naked, mostly-painted cyclists who precede and overwhelm the Fremont Solstice Parade each year are one of my favorite groups to photograph.  They are colorful. creative, joyful, and high-energy.

Last year I decided I needed a photo of every single Solstice Cyclist.  (Does this seem familiar?)  I had two reasons:

  1. Statistics. Photographers’ galleries contain mostly women. Is this disparity caused by population imbalance or by selection bias? Solstice Cyclists are famous for being naked cyclists, but some people wear some clothing. How common is that?  What protective device is more common: bike helmet or sunglasses?
  2. Source data for grammar. I want to expand my bodypaint generator to use graphics, and I want the generator’s output to mirror actual paintjobs. Once I identify all the different cyclists, I can study their paintjobs, break them down into parts, and put those parts back together in novel but believable ways.

I got a tripod and a timer so one camera could automatically photograph everyone who passed while I did my normal photography beside it. I had to juggle a surprising number of factors to place that camera properly.

  • To avoid being blocked by spectators, the tripod needed to be either right next to the street, or high enough to shoot over their heads. I saw a few balconies, stout tree branches, even a bridge, that could get the needed height, but that brought new problems. Most paintjobs photograph best from the front, and bicycle riders tent to lean forward, so a camera that is too high has a bad angle. Also, accessing those high places is non-trivial, so I opted for a front-row seat.
  • Aiming down the street at approaching cyclists is my usual MO, but an automated camera will have trouble with that.  Since the camera is looking down the street, cyclists in the same image can be 10 feet or 100 yards away. How does the camera know which one to focus on, and which ones to leave blurry?  Cyclists in front will obstruct the camera’s view of cyclists behind them.
  • The route turns a few times. Maybe setting up at a corner will alleviate these issues. Setting up just after a corner sets a maximum distance at which cyclists will appear. Any further and they’d be in the crowd. There’s still the problem of cyclists approaching the camera and filling the frame, blocking other cyclists.
  • What about aiming across the street?  Cyclists will stay about the same distance from the camera as they cross the frame, and they are only 3 or 4 abreast, as opposed to unlimited ranks front-to-back, so obstruction is less of an issue.  Since I’m as far forward as possible (so spectators don’t stand in front of me) cyclists on the near side of the street will be very close. My lens might not be wide enough to capture their whole bodies, and they will cross the frame very quickly, maybe in between ticks of the automatic timer.
  • Thus, I decided to shoot across the street at the cyclists on the far side of the road. The frame is wide enough at that range that I’ll get several photos as each cyclist passes. Three-quarter to side view is not ideal, but still pretty good.  I had to accept cyclists on the near side sometimes blocking the shot, but it was the best I could do.
  • Oh, also! Position along the parade route matters as well.  The Cyclists circle back so they stay close to the parade (human-powered floats are much slower than bicycles). Near the end of the parade route, there are fewer spectators and no returning cyclists to block my view, but I only get one chance to see each cyclist, and some cyclists leave the route before then (mechanical failures, etc.) Closer the start of the route I get multiple chances to photograph each cyclist, but more obstructions.

The day before the parade I scouted the parade route, looking for places to set up.

I chose the spot on the right, which is near the “center of the universe” sign on the east side of Fremont Ave. The tree gave some protection to the tripod. It’s a lot easier to accidentally trip over a tripod than it is to walk into a tree.

During the parade I kept looking over at the “shots remaining” counter on the tripod-mounted camera like the marines watching the sentry guns in Aliens.  “That number is going down.  It, it keeps going down.  Are we going to run out before they stop coming?”  The automatic filled a 32GB memory card and I had to swap for another in the middle of the parade.  Whenever a traffic jam stopped the stream of cyclists passing me, I’d pause the automatic camera to save disk space.

In all the automatic camera captured 2644 images.  That’s equivalent to an entire day of Atlanta Fashion Police, except it took only 63 minutes, not 16 hours.  I took an additional 1400 photos with the camera I was holding.

I considered using computer vision to help me identify cyclists, but even nudity-detecting algorithms were bamboozled by the cyclists’ coloration. So I couldn’t even get “Yes, there is a person in this photo”, much less, “There are 6 people in this photo, and the guy with the red stripes and sunglasses has appeared in 3 other photos.” Time to use my eyes, the best pattern-recognizers I know! I thought I could store all the information in a CSV file. I’m only recording a few pieces of data for each cyclist, do I really have to make an SQL database with webforms to search and update it?

1064 rows later, I realized that, yes, I did need that DB.  Since cyclists could make several laps, and I was gathering data from both cameras, I needed to check for duplicate cyclists often.  Ctrl-F in a spreadsheet wasn’t cutting it.

Next time: building that database, and a few insights from the data.

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