“Nothing’s occurring in animation – You manufacture everything.”
Gore Verbinski, film director
The animation industry is rife with technologies and techniques to speed up or enhance the animation production process. Every month, various innovations pop up across the world with the promise of guiding animators to improve their animation styles or develop impressive techniques.
These steps forward show that the animation industry has come a long way from the days of manually drawing frame by frame, nanosecond by nanosecond, in order to create an animated video. Animators can now create different characters, styles, and designs in no time.
From the relatable digital art you see on social media to the computer-generated animated films and series, animators have been able to make tons of creative and cultural contributions, impressing their mark on the world and inspiring lots of kids to do the same –– All thanks to the innovations in the animation industry.
And among these innovations is artificial intelligence or AI. Like most innovations, artificial intelligence helps animators create and design, particularly 3D animation models, in less time and with less effort.
An example of AI is the lip sync feature in Adobe sensei, which automates the mouth of your animated characters when you add voice-over audio over it. The Adobe sensei artificial intelligence and machine learning technology was developed by Adobe and designed to “collapse the time between marketing ideation and execution.”
From AI comes the component of machine learning animation. But what is machine learning animation? Does it differ from artificial intelligence? And what are the benefits of using machine learning animation?
In this blog post, we’ll share with you the value of machine learning animation and how animators and animation studios are using machine learning animation to their advantage.
What is Artificial Intelligence?
GIF by supercompressor via GIPHY
Before we zoom in on machine learning animation, let’s look deeper into artificial intelligence.
Artificial intelligence is the science of using machines and computers to solve problems and make decisions similar to the human brain.
They operate by taking in large data and analyzing that data for patterns and correlations. The information is then used to make predictions and come up with solutions.
A popular example is your phone’s predictive texts. The way your phones can guess what you want to say based on your past text messages.
In animation, AI is commonly seen in the areas of automation, virtual scene creation, 3D model creation, facial animation, and virtual reality.
Because of how popular artificial intelligence in animation is, animation software and applications have been developed by big technology companies like Google and Adobe. Top examples are Adobe Sensei (as mentioned earlier) and Google DeepMind.
What is Machine Learning Animation?
Coined by IBM computer scientist and pioneer in artificial intelligence Arthur Samuel, machine learning helps solve problems at a rate and scale that humans can’t accomplish.
The term came about when Samuel created a computer program for playing checkers. The more the game was played, the more the program evolved. It improved from playing experience and used algorithms to predict your moves.
So basically, machine learning animation is a component of an artificial intelligence application that enables its system to learn and adapt from experience rather than from being programmed. You may say that machine learning animation functions similarly to how human brains function.
GIF via GIPHY
When it comes to improving the animation process, machine learning animation can do so by predicting the next animated frame from the current one, also known as learned motion matching, predicting 3D key points from 2D animated videos, and many more.
Motion matching is a tool for animating characters. The downside is that it can drastically affect your system’s memory usage, using up more and more storage over time. Fortunately, there is now a system known as learned motion matching. Thanks to machine learning, motion matching-based animation systems are able to use less memory than usual.
What Are The Benefits of Machine Learning Animation?
GIF by britanniaonepix via GIPHY
Machine learning animation has transformed not only the landscape of animation but the world. Animated series and films have been completed in record time. Video games have become more immersive. Animated characters and movements have become smoother and more realistic.
As an animator, there are different benefits to using machine learning animation. Here are its top three benefits:
Animate Faster And Smoother
GIF by the_animal_crackers_movie via GIPHY
The goal of innovation and technology is to help people accomplish work faster and more conveniently. In the beginning, animators would have to manually sketch their various frames. The average number of frames in animation is 24 to 30 per second. This means that a simple five-minute animation would consist of a thousand frames –– a thousand drawings.
However, thanks to technology and machine learning animation, animators are able to create 30-minute animations and even complex animation styles more efficiently.
Take rotoscoping. Rotoscope animation is the process of tracing live-action video footage frame by frame in order to create specific sequences in animated videos. Some consider rotoscoping cheating but it’s actually a legitimate animation technique. Many animation studios, such as Disney, have used rotoscoping in making their animated films.
GIF by matthiasbrown via GIPHY
Rotoscoping added production value to animated videos and shot the state of early animation into the future. The problem? It can be incredibly time-consuming and tedious for animators. Imagine drawing all those little nuances and curves in live-action videos.
Enter machine learning animation.
Machine learning animation has streamlined and automated the rotoscoping process.
Animation studio Laika Studios has partnered with Intel to develop the machine learning animation software –– a 3D modeling program –– that does so. From spending five to six hours on 70 frames to accomplishing it in five quick minutes, the machine learning animation program has shortened the rotoscope animation process.
Now, not only has the animation industry been creating impressive visual effects, they’re doing it faster and having more fun. Production time is cut and the workload has been significantly reduced because of machine learning animation.
Encourages Creativity
Because your workload as an animator has been reduced, you can now focus on attracting more clients for your animation studio or coming up with creative stories and animation styles.
In other words, you’ll no longer be caught up in its more tedious tasks so you can explore the more creative aspects of animation. Machine learning animation opens up new possibilities for you as an animator. You can try out new animation styles, work on bridging your animation skill gaps, or improve your animation skills in general.
Although there may be a bit of a learning curve, once you get the hang of machine learning animation, you can also use it to explore other animation niches. How is this so?
Thanks to machine learning animation, you’ll be able to develop your animation skills. This will lead you to try out various animation techniques that you can use in other fields such as medicine and healthcare, sports, entertainment, and many more. This will diversify your freelance animation career.
Additionally, because you’re allowing your creative juices to run wild, you might even combat burnout. Burnout usually results when you’re constantly overworked and doing activities that drain your energy. In animation, this translates to spending long hours on exhausting tasks and redoing everything to perfection.
But because machine learning animation has you covered, you can direct your attention to other aspects of animation.
Create Better Facial Expressions and 3D Animation
GIF by creaigpickard via GIPHY
One of the more difficult yet important tasks in animation is creating natural facial expressions on your animated characters.
The right facial expressions with all their subtleties will make your story more realistic and impactful. Plus, audiences can easily recognize off-looking expressions. This can ruin their experience and harm your animation studio’s reputation.
For these reasons, animators usually spend hours perfecting their characters’ facial expressions and reactions, especially when it comes to 3D animations.
But with machine learning animation, animators can now generate more accurate and natural 3D models and facial expressions in no time.
Most notably, we have Disney studios and its semantic deep face model that’s able to design, simulate, and manipulate 3D animation faces. It’s considered a nonlinear 3D face modeling method. This machine learning animation learns a “network topology that maps the neutral 3D model of a face into the target facial expression.”
GIF by TokkingHeads via GIPHY
Disney has basically created an intuitive machine learning animation system that allows animators to create highly realistic 3D facial expressions and identities in a quicker and more efficient process.
Another example comes from the animation technology startup Midas Interactive.
They have developed Midas Creature, which is a machine learning animation engine that can create complex 2D and 3D animations. This can be used when animating for both films and video games.
With Midas Creature, machine learning animation is used to help animators manipulate complex 3D character animations. Animators can design smooth 3D characters and natural facial expressions with lesser costs and quicker production time.
How Are Animators Using Machine Learning Animation?
With the evolution of technology over the years, the world has seen more and more wild ideas come to life. Decades ago, the idea of machines adapting, thinking, and operating similar to a human brain would’ve been beyond an ordinary man’s dream. However, thanks to technology, we have artificial intelligence.
Machine learning animation is a component of artificial intelligence that aids and assists animations to do their work efficiently and with fewer costs.
Take Adobe Sensei and Google DeepMind. The animation process is now more streamlined as these machine learning animation software helps animators in the areas of automation, virtual scene creation, facial animation, and many more.
Additionally, animators can direct their attention to other matters such as expanding their animation studio rather than the tedious and repetitive aspects of animating.
Furthermore, there are three benefits in using machine learning animation. First, you can animate faster and smoother. Second, you can allow your creativity to flow better. And third, you can create better 3D models and facial expressions.
As technology continues to evolve, there’s no telling what the next big thing is. But you must be ready to make the most out of it as an animator.
Whether it be a new animation machine or software, you must learn its ins and outs. This will be beneficial both for the growth of your animation studio and your development as an animator and creative individual.
For more tips on developing your business skills as a freelance animator or animation studio owner, you can join our informative free masterclass, download a copy of our free marketing handbook, and check out our blog on “How to Start an Animation Studio”!
