PhotoXplore Helps You Shoot Manual

Explanation of shutter speed

Typical explanation of shutter speed

This quarter I took a class in Information Visualization, a topic I introduced in this post. I was particularly interested in ways to visualize information related with photography. One obvious component of photography that we don’t get to see often is how the photographer got the shot i.e. the settings he used.

While many sites, such as Flickr, let you view the EXIF information in the photos, there’s no easy way to view them for groups of photos, or get a sense of what settings people use for a certain genre of photography.

For example, say you’re at the Eiffel Tower and want a beautiful night shot and you’ve got your brand new DSLR out. But despite your best efforts at plowing through explanations of shutter speed and aperture, the crazy fractions and notation continue to defy you. That’s where my project, PhotoXplore, fits in.

Shimona's Photos on PhotoXplore

Shimona's Photos on PhotoXplore

Basically, the idea is that by visualizing the images in a simple interactive chart, you can make connections and begin to understand the relationships without needing to understand the numbers… for now at least. You can explore the chart by highlighting areas (called brushing) and watching the gallery area change. Vice versa, if you see an image you like, you can mouse over it and see where it pops up in the chart area.

The quarter system is way too short for a full project, so I wasn’t able to do any user studies, but I did notice some fun things while using it myself. For one, by plotting different photographer’s work, you can see what settings they like to use. Apparently, I like to stick to wide apertures and handheld photos – knowing this motivates me to branch out a bit.

Photos of Northern Lights

Photos of Northern Lights

I discovered another cool thing while exploring the Iceland Landscape photo set. There was an interesting clump of photos in the one area of the chart that was somewhat separate from the rest of the photos. On brushing over them, the gallery immediately repopulated with photos of the Northern Lights! It was immediately clear that to shoot the Northern Lights you need a wide aperture and a very long exposure. This little discovery captures the concept behind the PhotoXplore interface – it aims to provide a fun way to explore photos where the images and the settings are presented together making such discoveries easy and intuitive.

Quick disclaimer, all images are off Flickr using their API and credit goes to the original photographer. If you click on an image in the gallery, you can link to the original page on Flickr. Also, it’s not complete yet, I’d really like to let users come up with their own searches and save them, but for now its pre-populated with some sets of data. If you’d like a new set of images added, I can generate it and add to the list. Check it out and let me know what you think!

Visualizing Photography

Think of the thousands of photos on your computer, gigs of music etc… You’re not the only one, businesses and the government generate massive quantities of data such as statistics or financial information.¬†Information visualization is a new way of tackling the massive stream of data that is produced on a daily basis.

To see some interesting examples, you can check David McCandless’ site at

Since I love photography, I am interested in being able to visualize the data associated with photography. So many software engineers are also avid photographers and so much data (exif, tagging, geodata) but surprisingly, there is not much visualization work available in the field of photography.

However I found one that I quite like from Eric Fischer. It’s a visualization of local and tourist photo geodata using the Flickr API. The blue marks represent photos taken by locals, the red marks by tourists. Here’s the full version for San Diego.

Tourists and Local Map of San Diego

Tourist & Local Map: San Diego. By Eric Fischer

As you can see, the major tourist destinations in the city are Balboa Park, the Zoo, downtown, the Gaslamp quarter, Coronado and SeaWorld. You’d expect the local data to point out secret, cool, sightseeing spots that only locals know about. But what I noticed is that it actually shows you the best places to hit the bars, University St. between Hillcrest and 30th, Adams Ave., Newport St. in Ocean Beach and Garnet St. in Pacific Beach.

If you think about it, most people are most likely to take photos when out with friends at a bar. In fact, looking closely at South Park, where I live, the one dense blue dot on the map clearly points at Juniper and 30th, the location of the Whistlestop Bar, Station Tavern and Burgers and Rose Wine Pub.

How cool is that? In a new city, you could use the red areas to decide what to do during the day, and the blue areas to find the best nightlife. This sort of unexpected information becoming apparent is the best part of information visualization.

Some of these patterns might become more obvious if this map were animating the data over time. Animated over a day, you’d be able to see the blue marks light up at night and make that relationship more obvious. Animated over a year, you could see the best times to visit (or more likely, avoid!) the major tourist destinations.

To see a wonderful TED talk on information visualization, check out David McCandless’ talk.