Monthly Archives: July 2009

July 30, 2009

Crowd-Generated Content (CGC): What Is It?

By Mok Oh

What is Crowd-Generated Content (CGC)?  To better describe what CGC is, I need to first discuss user-generated content (UGC) and crowdsourcing.

UGC is content — from text to multimedia — that is produced by end users and are publicly available.  It could really be anything from blogs to videos.  It has been a big buzz word for many Web 2.0 applications and platforms.  Many websites (e.g. Yelp,  TripAdvisor, Ning, WordPress, Typepad, Flickr, YouTube, etc.) built a platform on which end users can easily create, organize, distribute and search their content — hence the words “user generated.”

Crowdsourcing, on the other hand, is “the act of taking a task traditionally performed by an employee or contractor, and outsourcing it to an undefined, generally large group of people or community in the form of an open call” (Wikipedia).  This power of the crowd has been amazing in many Web 2.0 applications and platforms as well.

So what the heck is Crowd-Generated Content?  Given the right platform and tools, the crowd can produce relevant and focused content with specific intentions — the crowd becomes the unifying voice for a cause, instead of many users doing different things.  It’s the difference between Yelp (CGC) and WordPress (UGC) platforms.

Am I splitting hair?  I don’t think so.  Where UGC is a generic term for anything an end user publishes on the web, CGC has a focused intention.  And this point is very important for folks like EveryScape or Google or Microsoft, where we are creating a viable, scalable solution and platform on which the entire freakin’ world could be visually built.  That really requires a serious focusing of intentions and serious focusing of CGC.

In fact, I will argue (in the following blogs) that we first need Tribe-Generated Content (TGC) first (a la Tribe Sourcing), then Crowd-Generated Content to follow.  A good analogy might be that TGC is the skeleton, and the CGC is the muscles on top.

Stay tuned!

3 comments   |  tags: , , , , , , , | posted in Platforms

July 28, 2009

Panoramic Equipment

By Mok Oh

I’ve been taking panoramic images  for over 10 years, and I’ve been using various gears for taking them — cameras, lenses, rotating heads, tripods, and GPS.  Curious about what I use now?  Here’s my list.

Lens

My lens of choice is Sigma 8mm fisheye lens.  In general, I prefer the fisheye lens since the field of view is very wide, i.e. need to take less amount of pictures to cover the full 360 x 180 degrees; i.e. faster.

The optics is quite good, and we’ve had very few of them fail.  There’s some chromatic aberration, but typically stitching software takes care of that.

Sigma 8mm Fish Eye Lens

Sigma 8mm Fisheye Lens

Camera

My camera brand of choice is Canon.  We’ve tried Nikons but they failed a lot more for us under extreme conditions (ask me if you’re curious).  I currently use Canon T1i, which has a 1080p video recording capability. Awesome camera.

Canon T1i

Canon T1i

Because the T1i is not a full frame digital SLR, when used with the Sigma 8mm, the circular fisheye image is cropped.  But I actually prefer the crop for better “resolution” of the scene.

Panoramic Tripod Head

My choice for panoramic tripod head is Nodal Ninja R1.  It’s light, compact, sturdy, and precise. Also, because the mount attaches to the ring-mounted lens (see images below), you don’t have to worry about messing up the focus of the lens — I initially had some trepidation about this, but not any more.

Nodal Ninja R1 Ring-Mounted Camera

Nodal Ninja R1 Ring-Mounted Camera

So there.  What do you use to take your panoramas?  Care to share?

7 comments   |  tags: , , , , , , , , | posted in Cameras, panorama, Photography

July 28, 2009

A9 and Streetside: Why Did They Fail?

By Mok Oh
Amazon A9 Maps

Amazon A9 Maps

Before EveryScape and Google Street View existed (and yes, we were doing this before Google was), there were a couple of attempts of street-level photography by companies you might have heard of: Amazon and Microsoft.

Amazon had their A9 Block View (shown above) and Microsoft  had (has?) their Streetside.

My question is: Why did they fail?

In some sense, their intensions were the same as EveryScape and Google — to enable users to virtually see places, businesses, points of interest from the comfort of your browser for various use cases and applications.

One obvious “feature” difference is that they did not use panoramic imagery.  One could argue that panoramic imagery is more immersive and experiential.

Does panoramic imagery make that much of a difference?  Isn’t one of the beauties of the Web is that “keep it simple, stupid” wins?

Or are the users really looking for richer online experiences?  A better UI/UX (a la Apple and iPhone)?  Were their approach limiting feature wise?

More questions than answers, unfortunately.  Facts or biases, your feedback is appreciated.

3 comments   |  tags: , , , , , , , , , | posted in maps, Photography

July 26, 2009

Much Ado About Augmented Reality?

By Mok Oh
Augmented Reality Heads-Up Display View

Augmented Reality Heads-Up Display View

My question to you is, do you believe in Augmented Reality?

In many ways, the notion of augmented reality is similar to 3D in a sense that expectations have been set high, but it hasn’t quite delivered.  We expected HUD in cars that help us with directions and more; we expected augmented reality glasses that help us with what we are seeing — and we expected this to happen a decade ago.  Hm…

Recently, there’s been a lot of talk about iPhone 3.1 that will enable real-time overlays for applications like augmented reality stuff.  Definitely looking forward to what will happen there, and what type of innovations will be pushed from this community.

Personally, I think there’s a lot more innovation in technology and UI/UX for AR to succeed.  Image recognition algorithms are not robust enough for general scenes (like in our every-day lives), but when supplemented with GPS, compass, accelerometers, and other sensors just might work and be useful.

What do you think?

9 comments   |  tags: , , , , | posted in 3D, augmented reality, Mobile

July 23, 2009

HDR Part 2: Exposure Fusion

By Mok Oh

This blog is the second part of the previous blog on high dynamic range imagery.

Exposure Fusion (a.k.a. Enfuse) does not use HDR.  But it is related in a sense that it uses multiple exposures to create a nice “fused” image.  (So technically, “part 2″ is a bit misleading.)

Exposure Fusion was a paper by Mertens, Kautz, and Van Reeth in 2007, and you can learn more about the work here.  This technique basically bypasses HDR creation all together to create a wonderfully fused image.

Let’s just briefly discuss some issues with HDR (I will discuss some benefits of HDR in the next blog).  HDR “assembly” takes quite a bit of processing time and the file sizes bloat up big time — which also means longer time to load to any programs like Photoshop to do anything to it.  From there, you typically end up tone mapping the image anyway.  And don’t get some folks started on the pain-in-the-ass-ness of tone mapping.  Yeah, it generally sucks when you end up doing a lot of them by hand.

Exposure Fusion basically says, “that’s bullsh!t!” There’s no need to convert a bunch of files to something you won’t use, then have to convert again, only to spend the next 2 hours tweaking some parameters you don’t understand, that was named by some ivory-tower researchers (sorry guys ;-) ). Exposure fusion just creates a wonderfully “fused” image from your multiple-exposure set, which is the part I really like.

So, gettin’ down to the brass tax, if you have a hard time going from HDR, then back to LDR using some tone mapping operator that doesn’t understand you, then use Enfuse.  It’s one of the most consistent way to create an image from multiple exposures.  And, it’ll save you time and lots of disk space.

One caveat is that Enfuse is a command line tool.  If you don’t like that, you can find some GUI wrapper programs out there (e.g. Bracketeer).

5 comments   |  tags: , , , , , , , | posted in Cameras, HDR, Photography, post processing

July 21, 2009

High Dynamic Range Imagery (part 1) — What the Heck Is It?

By Mok Oh

So, you’ve heard some folks talk about “high-dynamic range imagery” or HDR, and you think you sort of understand it, or not really?  Well then, I hope to de-mystify it for you in a series of blogs.

In my previous blog, I talked (or more like bitched) about why cameras suck; and one of my reasons was that they lacked sufficient dynamic range in capturing light.

“…, let’s talk about dynamic range.  This is the whole problem of the images above.  We’re only stuck with 0-255 per RGB channels.  This means that we need to describe the brightness of what we see — from dark shadows to sunlight — within the integer range of 0 to 255.  Even RAWs don’t cover it since the dynamic range needed to describe what we see could be 0-1,000,000.  Yes, cameras suck.  There are high-dynamic range imagery, and I will talk more about that soon.”

As shown above, there are series of photos that describe this problem.  In the beach shot 1, you see that the exposure was very long, so most pixels are washed out, but you can still see some contrast in the dark parts of the palm trees as well as the dark shadows on the sand ridges.

As the series of images get darker, e.g. beach shot 2 and beach shot 3, you can see the scenery much better, but the bright area around the sun is still too washed out.  By beach shot 6, we can see some outline of the sun better but everything else is now too dark.

Somewhere in this series of variously-exposed images lies the “right” answer for the composite image — this is the dynamic range problem.  Our eyes can see much better contrast than any of these camera shots (also because we can dynamically adapt better too, but that’s some other blog).  You can imagine manually photoshopping these images to get the solution image you want.  A more automated way is to create a single high-dynamic range image from this series of images, then tone map it.

Putting aside the technical lingo bullsh!t, I hope I’ve convinced you that there is a way to combine these images somehow to get the final image you want. (And I won’t bore you with the tech details either — if you must know, let me know pls.)

There are nice software products to do just this: Photoshop, Photomatix, and Enfuse.  There are more, but these are the ones I like.  (If you have your favorite, please comment and share!)

Beach shot "solution" using Photoshop

Beach shot "combined solution" using Photoshop

Beach shot "combined solution" using Photomatix

Beach shot "combined solution" using Photomatix

I’m not showing Enfuse just yet since it really isn’t HDR.  But I’m gonna stop right here for now, since the blog is getting too long.  I will talk more about Enfuse and more of HDRI-related issues in part 2 of this series.

13 comments   |  tags: , , , , , , | posted in Cameras, Photography, post processing

July 20, 2009

Why Do Cameras Suck (Compared to Our Eyes)?

By Mok Oh

Why can’t the cameras capture what we see how we see?  In most cases, my digital camera pictures don’t correspond well with what I am actually seeing.  For instance, when I look out the window, I can see the bright outsides as well as the insides fine with my own eyes. BUT when I take a picture, I’m either stuck with a blown out window or dark interior.

Why the f#@! is this, you may ask?  More technically in this case, it’s because cameras lack the dynamic range of our eyes.  More universally, it’s because cameras suck compared to human eyes (and we don’t even have the best eyes in the animal kingdom!).

My point is that cameras have a long ways to go before we can start capturing images that fall within the standards of what we actually see everyday.  Isn’t that the point?  I feel like we got stuck with the limitations of technology, and seem to have forgotten the whole point of reproducing how and what we see.  Yeah, cameras are getting better all the time, but not fast enough and not close enough yet.

So what are some “parameters” of the camera we can improve?  There’s been a lot of research in optics, vision, perception, etc., but I’m writing a blog and not a research paper (thank goodness it won’t be boring — hopefully).  I’m going to only talk about the following parameters:

  • Resolution
  • Focal length
  • Dynamic range

There’s definitely more, and I found a nice link here with interesting data.

As for human eye resolution, it is about ~600 mega pixel resolution.  Man, cameras are not even close to that!  Sure, you can create a panorama, but I’m talking about doing this in a single shot (or at 30 fps!).

Focal length wise, the article puts our eyes at about 16-22 mm.  Basically, our eyes can see a lot all around.  Do a simple test: put your hands out straight, wiggle your fingers, then start to move your arms to the opposing sides while looking straight.  I can see to about 180 degrees horizontally.

Finally, let’s talk about dynamic range.  This is the whole problem of the images above.  We’re only stuck with 0-255 per RGB channels.  This means that we need to describe the brightness of what we see — from dark shadows to sunlight — within the integer range of 0 to 255.  Even RAWs don’t cover it since the dynamic range needed to describe what we see could be 0-1,000,000.  Yes, cameras suck.  There are high-dynamic range imagery, and I will talk more about that soon.

These things basically mean, to me anyway, that our typical camera lenses are not wide enough, we need a lot more resolution, and needs a lot more dynamic range.

Are there more parameters we can hope for?  Of course!  What do you wish for in the next gen camera?

5 comments   |  tags: , , , , | posted in Cameras, Photography

July 18, 2009

Arc de Triomphe Photography with My iPhone

By Mok Oh

One way to get more resolution or field of view is to create a panorama — take more photos and put them together.  My previous two posts have been about this, and am following up with a few more examples of Arc de Triomphe in Paris.

As I’ve mentioned before, I used AutoStitch on my iPhone 3G S.  Much of the panoramas were an experimentation of adding some time and positional elements, which resulted in pretty cool stitched photos.

To get what I call the time element, I stayed in the same place a few minutes waiting for dynamic elements of the scene to change — e.g. cars, people, clouds.  By doing this, things that are static remain more solid and things that move have a ghost-like quality to them.

To get what I call the positional elements, I tried to focus on a feature as I walked along a path.  In these examples, I focused on the Arc while moving towards it.  This tends to create an impressionist-painting-like effect.

4 comments   |  tags: , , , , , , , , , , , | posted in Mobile, panorama, Photography, post processing

July 16, 2009

Paris, the Visual City

By Mok Oh
More Paris

Paris shot from inside a car

More often than not, I find that a typical field of view of a camera is not enough.  Using my iPhone 3GS, I cannot help but create panoramas and mosaics to get a wider field of view or to tell a “story.”

I am visiting Paris on a biz trip and below are some examples of mosaics I shot using AutoStitch app on my iPhone.  If you have not been to Paris yet, two words for you:  You must.  It is such a visual city with incredible amounts of beautiful sites all around.

Rue du Nil, Paris.

Ghosts walking on Rue du Nil, Paris.

Preparing for some car-mounted photography in Paris

Preparing for some car-mounted photography in Paris

Dinner in Paris

Dinner in Paris

Paris

Paris

7 comments   |  tags: , , , , , , | posted in panorama, Photography

July 13, 2009

AutoStitch iPhone App

By Mok Oh

I wanted an app on the iPhone that stitched mosaics/panoramas on the iPhone without having to off-load anything.  So, I searched the App store for “panoramas” and found a bunch, and tested them.  I found three apps that I liked:

  1. AutoStitch
  2. Pano
  3. PanoLab

My clear favorite was AutoStitch, since it seemed to be the easiest to use.  All I had to do was to select a bunch of photos that I took for a panorama, throw them in a “bucket,” and then click “stitch.”  After crunching away, it created some pretty awesome stitched mosaics.  All photos that you see posted here are stitched using AutoStich.  Definitely try it out.

3 comments   |  tags: , , , , | posted in panorama, Photography, post processing

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