Research write-up

Over the course of my photomosaic project I have needed to do a bunch of research into the art form and the available software out there.

Most of the software/services that I found either didn't match images very well (see app i. Accurate matching), only match to a grid (see app ii. IPA vs API), scale everything down (see app. iii. Scaling up) or repeat images (app iv. How to avoid repeats).

I found someone who claims to be the "inventor" of the photomosaic here, and while, yes he has photomosaics, they are all only matched to a grid.

I found a photomosaic stiching program called mazaika, and while the feature list is quite impressive, it has less accurate matching than my sofware and only matches to a grid. It also uses the (terrible IMO) feature to mask bad matching, where it colour corrects the images to the reference image.

I ran across an interesting method of grid mosaic tile matching using a "nearest neighbour" algorithm. This leverages machine learning to create a satisfactory result, however it does so to an approximation accuracy rather than an exact one. Also the creator has a good flow for generating tiles.

I've also read up on some of the other methods that people have used to create mosaics both online and offline, most of them only use one technique and/or modify the source images rather than arranging them.

Here is a quick list of some of the options that I investigated:

• http://www.theartoftylerjordan.com/make-an-easy-photo-mosaic-in-photoshop-2/
• http://www.mazaika.com/
• http://tvldz.tumblr.com/
• http://www.photomosaic.com/portfolio.html
• http://mosaically.com/
• http://www.canvaspop.com/photo-mosaic
• http://www.mosaizer.com/

New AV work in progress

Now with 100% more screenshots!!!

Part of the work that I've been doing with John Mackey has involved programmatic music analysis, and one of the things that I started doing was experimenting with some older code to see some of the results I could get out of it.

One of the projects that I settled on first was a failed experiment to transpose my Squiddy type things into 3d. Unfortunately, at the time I wasn't as experienced as I am now at manipulating vfx and using sound to control things and so the experiment didn't leave the "basic shapes" phase.

Now however I have the resources and skills to turn it into an actual work, and I've been able to leverage shaders and physics systems to my advantage to produce a really nice work that I'm really proud of.

The flecks in the "background" that you can see in the screenshots are illuminated by a flickering light at the top right (the light flickers based on a random frequency), they all flow down and to the left, and are destroyed once offscreen. They can also occlude the main subjects.

The subjects themselves are actually a recursion tree, with each step linked to a physics object and mapped to the bins of a Fast Fourier Transform (linear not logarithmic unfortunately ). The result of that mapping is that the 2 spheres that represent each of those physics objects "pop" with the music i,e, they grow larger when their particular frequency is hit. All the subjects are allowed to go offscreen (to some degree) except for the primary subject. All the subjects have an emissive material bound to their wireframe to give them detail up close and have a bit of a glow.

Apart from that, the Depth of Field shaders focus is linked to the head of the primary subject and the aperture is set (small?large its just a number to me) so that there is only a narrow focal area.

Changed major video work

The work that I was previously doing for "Creative Possibilities in Video" was a work inspired by the book Flatland and Don Hertzfeld's "Rejected" animations, however... I'm not doing that anymore.

The reasoning behind this is that in my spare time, I've been making some music videos using software that I've written for a jazz musician called John Mackey. I now feel like these works are becoming some of my stronger works for the year and so rather than continue in an uphill battle pushing a time consuming animation project, I decided to pivot and change the project to be on these works.

A sample of one of these works:

.

Unfortunately Vimeo doesn't allow me to upload any more of these yet. So I am going to upload them at a rate of 1-2 per week.

Soon I will also publish a short demonstration of how I have been using this software to create things and some of the common tweaks to the source that I've done during the production of these kind of works.

Also an interview with John Mackey about the other half of these works will follow.

Finally got the colours right

The image processing algorithm I was using was actually sorting everything with dissimilarity valued over similarity, which was not so good (duh). This was all due to my stupidity in reverse sorting lists in the processing phase rather than the placement phase (essentially doing the right thing in the wrong place).

Either way its fixed now.
And I have another photo of Johnny Depp, again this breaks JPEG so this is a very scaled down

EDIT:

I also now have a Nic Cage image (again scaled horribly):

New Nicolas Cage

Massive scale flickr integration into the get_images.py
This image at full size breaks JPEG size limits, so this is a scaled down version.

Depp

I pointed my program at flickr with the tag and search query of "Johnny Depp":

New Nic

I modified my algorithm to evolve and modify the parameters based on how close it is, and then email me the results.

Next step is flickr integration.

Some new Nic as well: