Archive for September, 2009

How To Take Club Photos

// September 28th, 2009 // 35 Comments » // Photography

I’ve been taking club photos for TillLate in London for half a year now, and I tried a few times at Club Illusion in Tartu, Estonia before that.  Early on, I remember struggling to find any good tutorials – as it turns out, the basics are pretty easy to understand.

What Are You Trying To Capture?

First up, consider why you’re taking the photo – to make the club look good:

f4.5, 1/4, ISO 800

For a straight club, make sure you are prioritising the following (in order):

  1. Hot chicks;
  2. Famous DJs (if any);
  3. People having fun (mixed groups, couples, interesting blokes);
  4. Cool venue.

What Kit Do You Need?

Very little, in SLR terms:

  • D-SLR camera with M(anual) mode and RAW picture format;
  • External flash with E-TTL (ie. an automatic mode);
  • Something to soften the flash – maybe a Stofen Omnibounce, or just a DIY bounce card.

You can in theory take club photos with a built-in flash, but you’ll look amateur and so will the photos.  Your choice!

f5.1, 1/10 second, ISO 800

Note that good flashes have Infrared assisted focus – they fire a red beam at the subject to work out the focus, which would take forever to find without the flash.  This is invaluable.  Make sure the focus assist works in Manual mode – for some stupid reason the cheapest Canons will let you use Manual or IR assist, but not both.  Ridiculous.

What Settings Should You Use?

Steal settings – track down club photos you like and read the EXIF data!  On Flickr, you find a “More properties” link it below the picture on the right:

How to find EXIF data in Flickr

To get started, all of my example pictures in this article include an overlay showing the settings.

Settings for People Photos

The first thing to realise – the flash only lights the people in the foreground. It simply isn’t powerful enough to light the room, and you don’t want it to!

f4.0, 1/6 second, ISO 800

If you just use the camera’s automatic P mode, it will expose for the foreground and the background will go black. To get that colour, turn to Manual mode.  Set a relatively wide apperture (f2.8 – f5.1) and a relatively long exposure (1/6 – 1/13 second) with a fast ISO (round 400-800).  Turn off any Image Stabilizer your camera or lens has, it will slow down focussing and gets confused by background movement in the longer exposure.

f4.0, 1/13 second, ISO 800

Your flash will freeze the foreground, whilst the longer exposure allows the background lighting to soak in and add depth.  Where possible, position the subject(s) between you and the lights so you maximise the spread of that colour.  Smoke, low ceilings, decorations and people in the background all provide surfaces to maximise that colour.

f4.5, 1/10 second, ISO 800

Remember to always show the photos to your subjects – always appreciated!

Settings For Crowd Shots

Don’t take every photo with the flash. You want a smattering of longer exposure pictures without a brightly lit person in the foreground – either pick up something solid like the DJ booth or just blur the crowd:

f4.0, 1/3 second, ISO 400

The beauty of digital is that you can just chimp away with different exposure lengths until you find something that works.  If you’re uncertain use the Info view of the photo to see the image histogram, which will tell you when you have a reasonable exposure.

f4.0, 4 seconds, ISO 800

Settings for Bar Pictures

Relatively long flash-less exposures can also pick out the neon often lighting bars:

f7.1, 1/5 second, ISO 800

Processing The Photos

Always shoot in RAW instead of JPEG – correct exposures are hard to hit when in manual mode with variable club lighting going off at random, and RAW gives you a much larger safety margin. You’ll need good processing software as well – I find Adobe Lightroom is pretty quick and easy whilst having a lot of power.

f4.0, 1/8 second, ISO 800

Don’t be afraid to crop out black backgrounds, and use tricks like adding Fill Light to pull out extra background colour which isn’t initially visible.

Finally, below you can see examples of my club photography improving over time – from the first shoot in Estonia to some relatively recent ones in London (the latest are here).  Practice really makes a difference – good luck!

Square Kiss Hair Girls Pucker Couple Feisty Face Scrunch Dancers Pole Dancing Blonde, Brunette Mine BJ Slowdance Look Me In The Eyes Fingernails Mirror Mirror Happy Clubber Illusion Green Smile Attitude Little & Large DJ Taps Couple Cyan Lights Purple Grrr Hmmm Smile Chicks DJ Pout Tiger Dancers Hand Stairs Red/Blue Green Three Card No Dancing On This Surface Hair Strobe Funky Chicken Green Pink Finger

Portfolio: web site

// September 13th, 2009 // 1 Comment » // Web

I’ve just finished a quick hack of Typebased, a free WordPress theme from Woo Themes, to nicely frame Youtube videos for web site

We decided that starting from someone else’s theme was the only way to get a site up and running on a shoestring budget.

The header photo is one I took from the top of Centrepoint at dawn, carefully edited to remove any iconic London buildings and convey the sense of an unknown city coming to life.

Masabists: Hacking AdMob Stats

// September 3rd, 2009 // No Comments » // Mobile

This post was originally featured on the Masabists blog, and was voted joint top post in Carnival of the Mobilists #190.

Handset statistics are notoriously hard to come by – only the operators know what handsets are actually being used by all customers on their network, and they won’t tell. Every other purveyor of statistics has an inherent bias, which makes them more attractive for some analyses and less for others. For example:

  • GetJar make comprehensive statistics available for who is downloading applications from their site and have huge cross-operator volumes of downloads
    • …but many of these are downloaded via the web and synced through a cable, a highly unusual activity for most mobile users
    • …which puts a huge skew on the data – I’m pretty certain Amoi aren’t actually larger in the UK market than RIM’s Blackberry.
  • Bango publish a Top 20 handsets list every month or so, with a skew for their operator relationships
    • Top 20 is great but there are plenty of handsets below that which are still worth supporting
  • AdMob have some immensely detailed metrics reports, but again the operator partner skew was always very visible
    • I’m just not convinced that anything by ZTE is actually in the Top 10 most popular UK phones!
    • I’m also unconvinced that the iPod Touch is much more popular than the iPhone…

User Profiles

All of these statistics have great value, but none of these companies can actually give an overall picture fo the entire market. Each set will be skewed heavily based on the type of user attracted to the service and the operator relationships that service has. To find out the overall market picture fudge them all together and treat with care – but by profiling each site you can find out more useful information for specific needs.

AdMob, as the main provider of mobile web advertising, offer a very good view of the mobile data user, who would also be an obvious early adopter of any mobile service requiring net access, be it web-based or a networked application.

Traditionally, AdMob have just given a Top N list of device models and some aggregate manufacturer numbers, which were never enough to tell anything useful – their strong relationship with MVNO Three clearly led to some very obvious weird “popular” handsets showing up and called all of the data into question.

I had always dismissed them at this point and moved on. Fortunately, though, when you look inside the reports they publish per-operator statistics for each manufacturer – so we can actually derive some meaningful national conclusions!

Hacking The Stats

So – why hack? Don’t we have everything we need?

Sadly not – the July ’09 report is a very nice professional PDF given graphical summaries of the manufacturer breakdown per-operator, as a series of proportions in stacked columns:

AdMob handset statistics - UK operator split

Whilst it is flattering, as a Jersey boy, to see Jersey Telecoms given equal weight to Vodafone, I have a sneaking suspicion that the entire population of Jersey is equivalent to a rounding error when counting Vodafone’s UK customer base.

What we need is to convert these into national numbers, by weighting all of the proportions by the size of the operator. The only way to do this with the public information is to screenshot the graph from the PDF at the largest size you can get it, and count the pixels for every bar – tedious, but luckily for you I’ve done it for you.

Telecoms Market Research provide some useful figures from Q1 2008 for each operator (not up to date, but close enough for these purposes):

Once we aggregate all of these weighted proportions, we end up with the following rough proportions for manufacturers among early mobile web adopters:

Handset manufacturer proportions for mobile web users in UK June 2009, derived from AdMob statistics

It won’t help everyone, but hopefully it is of some use for anyone struggling for some statistics!

Please comment on the original post.