Compositing Goodness...

Following on from my most recent post (here), I continued to develop the scene I had been working on as a 2D image in Photoshop (using 3D renders from Maya).

I then added additional layers/objects to the Maya scene file and organised the appropriate render layers. Image sequences were rendered, and imported into After Effects, where a 10-second sequence was constructed - using the same 'style' as the prototype image.

The completed test sequence can be seen below;

Moving forwards, I would like to continue this visual development, perhaps with the addition of camera movement and depth-of-field techniques.

Having Fun!

In terms of technical development, my knowledge of 3D software, scripting skills and problem solving abilities have surpassed those that I need to be able to complete the projects I am currently working on.

This has given me the time and opportunity to focus on visual experimentation, bringing a bit more fun back into my work, and making it more interesting than searching through pages of MEL commands!

I have been experimenting with using the skills gained in the Going Live module, to enhance the output and presentation of my previous cell visualisation work - using my skills as a digital artist.

Starting with a previous data-set, I adapted one of my scripts to create locators instead of spheres. I then created a simple particle system and used a modified version of a script provided by the external examiner to 'attach' the particles to the locators. This meant that I could use Maya's own 'metaball' system - not strictly metaballs, as it is a particle render type called "Blobby Surfaces", but it gives a similar effect. The image below shows a beauty render of the blobby surfaces;

Once this model had been created, I started to experiment with shaders. After reading some articles in this months 3D Artist and 3D world magazines, I created an MIA mental ray shader, and added a mental ray fast skin shader (normally used for subsurface scattering) and adjusted the colours and attributes to create a suitable look.

I added lighting in the form of two area lights, which used the mental ray area light options to transform from squares into cylinders, 'wrapping' around my geometry. Decay was set to quadratic (to create more accurate lighting) and the intensity of the lights was increased significantly (around 4500 each).

The next stage was to incorporate dust motes floating around. This is something I could imagine in my head, but was not sure how to implement. I looked at adding this in post-production, but although this could be quicker, did not provide enough control (or use 3 dimensions). I created a new scene file and using a particle emitter, created a particle 'explosion' - the forces were then zeroed out, so that I had a static particle cloud. I added my own gravity and turbulence fields, and tweaked these until I had the movement that I liked.

Finally, I setup render layers to output the passes I wanted - a MIA shader pass, a second MIA with an outline style shader, and separate pass for dust motes. After rendering a single frame, I moved into Photoshop and started experimenting with compositing these passes together, to create the look I wanted. I also added some fake bokeh effects in the background, coupled with some randomly generated cloud textures. The final image can be seen below, looking entirely different to how it first started (above);

At this stage, I wanted to make sure that I could recreate this look with image sequences, so I started work in After Effects. Fortunately I was able to mirror this image in video form, and can swap in the rendered image sequences when finished. By working in AE, I realised that I would need to add a matte pass for the cell geometry. Below, a short video shows the breakdown of how this shot was constructed, and although static, shows how a final video could look;

I have thoroughly enjoyed this experimentation, and I have created something I am really happy with - something very different to the first attempts (which can be seen in an earlier post here). Although I don't yet see this as a finished piece, I can already see ideas developing, and it is good to try new techniques and methods of presenting the same mathematical data... more importantly it is good to get back to being an artist, something that I did not realise I missed until now!

Advanced Production (Summary)

Despite returning to Semester 2 later than expected (due to illness), I have made excellent progress, with major breakthroughs in overcoming many of the challenges my project was facing.

My programme of study takes a more visualisation based route, and I am working with the University mathematics division to visualise numerical data (gained from their mathematical models) which represents the growth and development of cancer cells (or solid tumour growth).

Working with numerical data has created it's own set of challenges, as Maya cannot read or interpret this in it's off-the-shelf form. As a result of this problem, I have developed skills in using Maya's own scripting language, MEL (Maya Embedded Language) and also a second scripting language (used more widely) called Python. Although this has been a difficult and time-consuming process (several months of learning, which is still ongoing) I have been able to harness this new understanding and create custom tools which can be used to read the mathematical data and create appropriate 3D geometry.

Throughout learning each scripting language, I referred primarily to online sources, and the 'official' documentation provided. I also used the Digital Tutors service, which was both informative and relevant, helping me overcome the hurdle of knowing where to start, and what to focus on.

Through creating my own custom tools, I was able to work with the numerical data-sets provided. Starting with simple tests, I was (eventually) able to construct fully animated scenes containing simple spheres, representing the individual cancer cells, and although time-consuming to process, these results opened the way for more advanced development of the data and it's visual attributes.

I spent some time experimenting with Maya's render layers, and compositing passes using Nuke. This was as a response to feedback given last semester - not everything has to be done in 3D, as it can often be quicker and easier to complete some work in 3D, but fine-tune the details in post-production. This helped me develop possible ideas for the look of cells, when considering texture on a microscopic basis, and I also experimented with 'faking' depth-of-field techniques to enhance this.

Although creating spheres was great, I wanted to push my skills further. I spent time working with RealFlow, Cinema 4D and Houdini - three great 3D packages. With the exception of RealFlow, these were entirely new to me, and although Cinema 4D was fairly straight-forward, Houdini had a very steep learning curve. Using my Python scripting skills, I created a large-scale metaball system, equivalent to the spheres created in Maya - this was a challenging task, forcing me to solve several problems, whilst trying to script in a language mostly new to myself. The result of this technical experimentation allowed me to create an interesting almost-organic 3D structure, which moved and behaved as one surface, instead of 1068 individual cells.

After completing these Python related tasks, I returned to Maya to work with additional data-sets, still showing the growth and development of cancer cells, but in a different format. This data would require not only animated movement of cells, but changing colours, and eventually, complex density 'clouds'.

The difficulty at this stage in my work, was the size of the data-sets... one of which contains over 30 million lines of information (a text file weighing in at around 800mb). Despite breaking this into smaller chunks of data, it was still computationally intense, and difficult to work with (often crashing high speed computers). I spent time streamlining and optimising my scripts, and the way they handled the data - as an example, my oxygen density script was originally taking around 350 seconds per frame to process, whereas now it takes around 90 seconds, about a quarter of the time. As I have learned more about MEL, and gained a better understanding of the language, I have been constantly improving and refining my scripts, to ensure the best efficiency when working with large data sets.

I am currently working with new additional data-sets, which again have constantly required me to think and problem solve... now that my scripts are optimised, I am confident that my scripting abilities are suited to a wide range of data types, across two very different scripting languages. This allows me to tackle upcoming problems with new knowledge, based on the experiences I have had over the last ~3 months, giving me a definite headstart.

In summary, my practice-based learning has developed the following;

• Scripting - both MEL and Python, for simple and complex tasks (including 3D visualisation)
• Improved software knowledge - Maya, RealFlow, Nuke
• New software knowledge - Cinema 4D, Houdini
• Advanced 3D skills development - particles/dynamics, data input/output, script optimisation, rendering
• Experience in 2D compositing with 3D-based image sequences

Due to the sensitive nature of the mathematical data I am working with (and as the source data is effectively the result of unpublished research) I am unable to post a large amount of my visual work online. However, this sensitive material will be made privately available during course presentations, and to module assessors as necessary.

Visible Progress!

Over the last couple of weeks, my role in the Going Live project increased significantly, and then stopped completely. All of the animated shots had lighting added, and then I added the render layers/passes and started feeding completed shots through the render farm (which was considerably faster than I expected it to be). Sound effects and music were then added by the sound team, creating our finished advert.

It took a long time to get there, and there were problems along the way, but I learned a lot (particularly about rendering and compositing) and I am glad we all got there in the end! Next week, we are due to meet with the company in their London studio and present our finished project - hopefully the feedback will be good!

As for my cell visualisation work, this has been making good progress since my role in Going Live has lessened.

The first data-set I was working with, which represented cells and fibres in 2D space, now has fully working scripts, which are streamlined to work efficiently (or to actually work at all!). I am currently awaiting feedback on the video outcome of this work, so that I can decide where to take this next.

The other data-sets (involving cells, blood vessels, and oxygen density maps) have made even better progress. Again, after optimising my MEL scripts, the amount of data (several million lines of information) has become manageable, although time-consuming to process. I am currently part of the way through 'translating' this data into Maya's 3D environment.

An example render from the cells file can be seen below. This example frame is approximately two thirds of the way through the cell data, and incorporates some 'noise' on the cell surfaces to break up the uniformity (an idea suggested by the mathematician who provided the data);

As for the oxygen density, I decided to continue using a single polygonal plane for this, with grid points in the data having a matching vertex on the 3D geometry. The data then lifts/lowers each grid point/vertex between 0 and 1, where 1 is the most dense area of the oxygen 'clouds'.

The 'look' of these clouds is then controlled using one of two shaders.

Shader 1 ("Clouds") is coloured white, and uses a vertically-aligned ramp shader for it's transparency value, where 0 is fully transparent and 1 is fully visible. This means that as points on the vertex grid are changed in the Y-axis, their transparency is also changed (as they are moved higher, they become more visible).

Shader 2 ("Bands") expands upon this idea, and uses a second ramp for the colour (from blue to red, low to high). The transparency ramp is also 'sliced' into bands which are evenly spaced vertically - this means that only the narrow bands are visible, giving us slices of colour (where the colour is defined by where the slice falls on the colour ramp, rather than a fixed colour). This gives a result similar to the high/low pressure bands which weather presenters often use, but with colour added.

I have included a video below, which better explains these shaders - the white 'cloud' is shader 1, and the coloured 'bands' are shader 2;

Although this video shows a top-down view of the scene, it is important to remember that these effects are generated in 3D - moving forwards, I could include moving camera or changing points of view to highlight particular events.

Also, the oxygen density visuals are considered another 'layer' which I can add to the cells and blood vessels, creating a more complete final output.

I am not sure as to how this final output will look at the moment, as I am still developing the visual elements of each of the data-sets, but progress is good and things are at least working now...

Needs more juice...

Similar to my last blog entry, my efforts are still divided between two main projects;

The Going Live project has been making excellent progress. The team and I have continued improving the visual outcome of the 3D elements. With a texture in place, lighting and rendering have started to progress rapidly. Animated shots are being lit, rendered and composited, so that final testing can take place.

Although I have taken on the role of CG Supervisor, I have been involved in other areas, and responsible for others. I was involved in tracking the camera footage and creating a 3D pre-visualisation of the sequence. I have monitored the 3D pipeline continuously, and offered advice and created fixes for problems - this includes working with others in modeling, texturing, rigging, animation, and lighting. I was responsible for creating a dynamic cloth system which would allow for easier animation, and I have managed the rendering process (involving creating render layers and using the render farm). Finally, I get to pass rendered scenes to the compositing team, who can work their magic... and before I know it, we will have finished the advert!

Returning to my cell visualisation work, I have reached a temporary plateau. I have developed my pipeline/workflow and have implemented new and improved scripts to manage the new data that I have received from my colleagues in the Mathematics division.

However, the vast quantity of data has been as proving difficult to process efficiently. After some development, I have speeded up the process, but this still takes a considerable amount of time to complete. Fortunately, I discussed this with my project supervisor/programme leader, and agreed the use of high-specification computers in the University, where I can process data quickly, making use of round-the-clock facilities. This week, I will begin using these facilities, to start working with this new data that I have received.

It is important that I begin this early, as the sooner the numerical data has been translated into 3D space, the sooner I can begin developing the visual qualities of the mathematical models. Completing this visualisation process becomes even more important, as the mathematical models will be presented as part of a conference in June - giving me a deadline to work towards...

More Data

Over the last couple of weeks, I have had to divide my attention between multiple projects.

The 'Going Live' project has ramped up into production, with modeling and rigging now complete. Animation has started, and texturing is currently underway. My role as CG Supervisor has been demanding, as all of these CG elements have been happening in quick succession. On top of this role, I was also responsible for implementing a customised nCloth dynamics system for our 'character'. This was created alongside the rigging process, to ensure that these components would work together happily, and after resolving a few technical problems, the system is now working nicely. My next task was to create and organise the appropriate render layers in Maya, ready for rendering and then compositing to take place (hopefully late this week or early next). Although I had worked with render layers before, this project requires more variants than I am used to working with, so has taken a bit of time to configure and setup properly. Despite all this work taking up more time than initially expected, the project has made good progress, and continues to do so.

After my meeting with mathematics last week (and several more since), my cell visualisation workload has increased also. I have received new data from both students, and I am currently in the process of writing scripts that will translate these into 3D scenes inside Maya.

The first new data set contains fibres (to be added to cells), which are based on xyz locations and xy rotations. I had not scripted rotation values yet, so this was a good opportunity to expand my knowledge of MEL. I am currently awaiting the full data-set for this part of the visualisation, so will continue to work on this moving forwards.

The other data set adds oxygen density to a scene containing cancer cells and blood vessels. This file contains over 30 million lines of information, and weighs in at around 800mb - making it rather difficult to work with. I have tried different approaches in visualising this data efficiently, such as adjusting transparency on cubes based on the density value or scaling particle clouds. Unfortunately, there are about 10,200 points per frame, so these methods take far too long to calculate. I am currently testing a new method, which creates a single polygonal plane, with the required number of vertices. The script then runs through each vertice, and moves it in the y-axis based on the density value (between 0 and 1). A ramp shader then adjusts the transparency of the plane based on the height (where 0 density is fully transparent). This creates white, cloudy patches where oxygen density is high. Although this still takes a long time to process, it is considerably faster than the other methods.

Most of this work is still on-going, and has 'arrived' at the same time, making it difficult to balance. Fortunately, I have been able to allow extra time in working on these projects, so hopefully the worst of it is over now...

On a more exciting note, three of my videos were used at an event in Dundee on Saturday 12th March. The videos are 3D visualisations of mathematical models which are being used to predict cancer growth and development, and were developed in collabroation with a PhD student in the University's mathematics division. They were shown at an event called "Sensational Women in Science" as part of the Women in Science Festival 2011.

Also, some of the other data I am currently working with will be presented at a large conference later this year (in June), so I have a deadline which I can work towards.

Snake In The Grass

...more specifically, a Python.

Continuing on from my Cinema 4D experimentation with metaballs, I abandoned that line of testing, as it wasn't going to be a viable option for the large amount of cells I was dealing with. Alongside Digital Tutors, I returned to Python scripting, trying to 'translate' my MEL script into something useable inside of Houdini.

After almost a week's worth of scripting, fixing things, and re-scripting, the Python/Houdini version of my data-loading script works, creating all of the necessary nodes in Houdini, and keyframing all of the animation. This allowed me to natively create metaballs, rather than try and convert existing scene information. Houdini handles metaballs exceptionally well, adjusting the viewport geometry on the fly (so it doesnt crash regularly like Cinema 4D). Using Mantra, I was able to render out the full 1900 frame image sequence, with frame 1900 shown below;

Although I am still learning to use Houdini, I have made breakthrough progress in using the software alongside Python, opening up a whole range of new opportunities. I have started trying to figure out shaders and lighting in Houdini (which seems more difficult than expected), and I created some example 'looks' for my meta-surface, shown below;

I am due to meet with the mathematics department this week, where I will present all of my research, ideas, and generated media - bearing in mind, that they have not seen any of the results so far. I am hoping that this meeting will help inform my next steps, and direct my technical understanding to a new visual solution.