animation Archives - Page 2 of 2

November 27, 2017 — 1 Comment

Houdini Junk Series | Peeling Clown

Here is Peeling Crown #013A from My Houdini Junk series. It created with Cloth and Growth Simulation in Houdini 16 and rendered in C4D's Octane Render.

My Houdini Junk Series Vol.01

My Houdini Junk Series are archives of my R&Ds which are self-produced / self-developed o I learned from blogs/web sites/tutorials. My Houdini Junk mostly developed in Pre/After Project processes or independently of this processes.

Check out all collection from : MY HOUDINI JUNK - BADQODE

What is Houdini?

Houdini is a 3D animation and special effects application developed by Side FX, a twenty-five-year-old Toronto-based company. Houdini is designed to create 3D animations and 3D effects in movies, TV, video games and virtual reality. Houdini is renowned for combining the worlds of film, TV, video games and virtual reality into one powerful platform.

The former flagship of Side Effects, PRISMS, a suite of 3D graphics tools, served as a foundation for Houdini's development.

Unlike other 3D animation software, Houdini uses a node-based procedural workflow that simplifies the job of making the updates you apply to the model while refining your work. Unlike programs such as Maya or Blender, it allows you to revert to a previous version in your work and update over the old version.

While Houdini is primarily used for dynamic environments and particle effects, it also includes a full set of tools for artists who want to use it in other areas such as modelling, animation or rendering.

Houdini | 3D Procedural Software for Film, TV & Gamedev | SideFX

What exactly does do?

Houdini is known for its advanced dynamic simulation tools that allow the creation of highly realistic visual effects. And it has an efficient workflow designed for small studios and individual artists.

New efficiency in software means cutting-edge effects can be achieved on less advanced hardware. What really sets Houdini apart from other 3D animation software is its computational nature.

Assets are usually created with a set of nodes algorithm. The advantage of this workflow is that it allows artists to create detailed objects in relatively short steps, unlike other programs.

Although Houdini is known for special effects, it includes all the tools that the best 3D modeling programs have to offer. Houdini also includes standard geometric models and animations.

The program comes with the powerful render engine Mantra, but it also supports 3rd party render engines like Renderman.

it has a node-based system that provides a flexible working environment for creating shaders and creating CG effects. It has a powerful system for creating smoke and fire simulations and a compiler for layered image effects.

Houdini offers scripting via various APIs, but Python is the language of choice for most packages. It allows the creation of custom tools and plugins, as well as built-in scripting and automation of specific tools.

Who uses?

Houdini is especially suitable for visual effects artists with a technical background. It provides all the editing tools expected in 3D software, but is known for its VFX tools and node-based procedural nature of its workflow.

Beginners note that features have a steep learning curve due to the procedural design. The key to success with Houdini is to have knowledge about mathematics and algorithms.

For this reason, Houdini is an easier program to learn for those with a background in programming and math, such as technical artists. For those who do not have experience in these matters, you can find many Houdini tutorials to improve themselves.

When you start using the program, if you are familiar with programs such as Autodesk Maya and 3DS Max, you will see that it is more flexible to use than these programs. And artists who can successfully learn the software will find that they produce many effects without the need for any traditional artistic interaction.

Teams will enjoy working with it because every part of the project can be easily modified at any point in the development process.

it offers a free version of the Houdini FX kit for students and hobby use to create personal and non-commercial projects.

While this version of Houdini lets you compose your work and save it to your computer, the only drawback is that it adds a watermark. You can download the Houdini Apprentice version for free here.

In which creative projects is used?

It's is a complete package for VFX studios working for games, movies and television. Its tools are powerful, reliable, customizable and designed for high-end production.

It means faster production and low budget power usage thanks to procedural workflow. For this reason, Disney is among the key users who use it in the films Frozen and Zootopia. Also, HBO's Game of Thrones uses it for some visual effects.

In the Video Game world, many video game studios also use Houdini. Games like Call of Duty and League of Legends are examples of this.

Houdini is a useful tool for creating simulations of clouds, smoke or fire, as well as liquids and fabric. Although Houdini can render any scene, the software is best known for its fluid-like effects and other simulations like it.

it is powerful when used to create complex simulations that use large amounts of data. Studios choose Houdini to create large special effects systems that integrate with complex scenes.

Studios often use software like Maya to handle modeling and hardware features and use it to integrate complex simulated effects.

Game designers, visual effects artists, and technical directors use Houdini daily to create state-of-the-art effects and enhance their work with simulated environments.

Check out our Digital Art Portfolio from
www.badqode.com

Ars Electronica 2016 – Honorary Mention

We are honored to announce that the jury of the Computer Animation/Film/VFX of Prix Ars Electronica : https://en.wikipedia.org/wiki/Ars_Electronica 2016 has selected our work: "Bio-Inspire FullDome AV Performance” for the Honorary Mention!
Thanks everyone!

Check the video if you haven't yet : http://prix2016.aec.at/prixwinner/17912/

Check out our showreel & portfolio : https://www.badqode.com

Ars Electronica 2016

“RADICAL ATOMS and the alchemists of our time” was the theme of the Ars Electronica Festival staged September 8-12, 2016 at multiple locations in Linz. The prime venue was, once again, POSTCITY, the former Austrian Postal Service logistics facility adjacent to the train station. It provided 80,000 m2 of exhibition space for conferences and speeches, exhibitions and projects, concerts and performances, animated films and awards ceremonies, guided tours and workshops. Here are some motifs conveying impressions of this year’s festival.
This was the Ars Electronica Festival 2016 – Ars Electronica Blog

Check Out our Latest Performance on Ars Electronica 2017 too !

Abysmal - Ars Electronica

Artificial Intelligence & Machine Learning Inspired Immersive A/V Performance - Ars Electronica / Linz

Abysmal means bottomless; resembling an abyss in depth; unfathomable.

Perception is a procedure of acquiring, interpreting, selecting, and organizing sensory information. Perception presumes sensing. In people, perception is aided by sensory organs. In the area of artificial intelligence, perception mechanism puts the data acquired by the sensors together in a meaningful manner. Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. Inspired by the brain, deep neural networks (DNN) are thought to learn abstract representations through their hierarchical architecture.

Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.

Deep learning emerged in the last decade and extremely changed and is still changing our current and future world. It refers to a ‘deep mining of data’ with so-called deep neural networks: neural networks having so many layers. What a net is doing is cascading simple linear transformations to represent highly non-linear functions that could efficiently extract the basic structures and patterns within the data and map to an output of ‘making sense of input’. Yes, neural Nets is a cascade of layers: Those are hidden: who knows what is exactly happening! As one adds more and more ‘hidden’ layers, so the network gets deeper and one makes it able to represent any function: they are universal approximators. But getting deeper comes with a price: more layers mean more parameters to tune. Learning millions of parameters requires big data, otherwise, neural networks will fail. The learning/tuning process is a game of step back and forth in the space of numbers with a well known back-propagation technique. This game is played in training the networks — just like training a human which learns from his experience — well, mostly from his mistakes.

A type of neural layer is Convolutional Neural layer which turns a network to a Convolutional Neural Network -- a neural network with particular ability to extract rich contextual information from image-like data, mimicking how a human observer understands the ’seen’ world, by expressing it in terms of non-seen, non-attended, non-humanly-expressible basic structures. How and why it performs far better than any other machine learning techniques and continues to even beat human-level performance is a hot topic and several technical proofs from optimization, probability, and statistics, mathematics, control theory, etc. perspectives are available, but it is still a pipeline of linear transformations, nothing more...

The work mostly shows the ‘hidden' transformations happening in a network: summing and multiplying things, adding some non-linearities, creating common basic structures, patterns inside data. It creates highly non-linear functions that map 'un-knowledge' to ‘knowledge'. As our time creates quintillions of bytes of information per day, how can we make sense of this huge amount of data? Let networks do it four ourselves. We give all the human knowledge and experience to the net then it will make sense of everything. As our life is becoming non-sense, maybe we expect NN to learn and give us the sense of it.

Check out our Digital Art Portfolio from
www.badqode.com

We are invited to Ars Electronica 2017

We are invited to Ars Electronica 2017, to make a 3d projection show in Deep Space 8K! Abysmal, is a 3d film about the learning alghoritm of an Artificial Intelligence. It will be screening on a 16 times 9 meters wall and once again 16 times 9 meters of floor. If you'll be around Linz/Austria between 7/11 Sept., we'd be glad to share the experience with you. Cheers!

Abysmal - Ars Electronica

Artificial Intelligence & Machine Learning Inspired Immersive A/V Performance - Ars Electronica / Linz

Abysmal means bottomless; resembling an abyss in depth; unfathomable.

Perception is a procedure of acquiring, interpreting, selecting, and organizing sensory information. Perception presumes sensing. In people, perception is aided by sensory organs. In the area of artificial intelligence, perception mechanism puts the data acquired by the sensors together in a meaningful manner. Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. Inspired by the brain, deep neural networks (DNN) are thought to learn abstract representations through their hierarchical architecture.

Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.

Deep learning emerged in the last decade and extremely changed and is still changing our current and future world. It refers to a ‘deep mining of data’ with so-called deep neural networks: neural networks having so many layers. What a net is doing is cascading simple linear transformations to represent highly non-linear functions that could efficiently extract the basic structures and patterns within the data and map to an output of ‘making sense of input’. Yes, neural Nets is a cascade of layers: Those are hidden: who knows what is exactly happening! As one adds more and more ‘hidden’ layers, so the network gets deeper and one makes it able to represent any function: they are universal approximators. But getting deeper comes with a price: more layers mean more parameters to tune. Learning millions of parameters requires big data, otherwise, neural networks will fail. The learning/tuning process is a game of step back and forth in the space of numbers with a well known back-propagation technique. This game is played in training the networks — just like training a human which learns from his experience — well, mostly from his mistakes.

A type of neural layer is Convolutional Neural layer which turns a network to a Convolutional Neural Network -- a neural network with particular ability to extract rich contextual information from image-like data, mimicking how a human observer understands the ’seen’ world, by expressing it in terms of non-seen, non-attended, non-humanly-expressible basic structures. How and why it performs far better than any other machine learning techniques and continues to even beat human-level performance is a hot topic and several technical proofs from optimization, probability, and statistics, mathematics, control theory, etc. perspectives are available, but it is still a pipeline of linear transformations, nothing more...

The work mostly shows the ‘hidden' transformations happening in a network: summing and multiplying things, adding some non-linearities, creating common basic structures, patterns inside data. It creates highly non-linear functions that map 'un-knowledge' to ‘knowledge'. As our time creates quintillions of bytes of information per day, how can we make sense of this huge amount of data? Let networks do it four ourselves. We give all the human knowledge and experience to the net then it will make sense of everything. As our life is becoming non-sense, maybe we expect NN to learn and give us the sense of it.

Houdini Junk Series | Peeling Clown

My Houdini Junk Series Vol.01

What is Houdini?

What exactly does do?

Who uses?

In which creative projects is used?

FOLLOW US

Ars Electronica 2016 – Honorary Mention

Ars Electronica 2016

Abysmal - Ars Electronica

Artificial Intelligence & Machine Learning Inspired Immersive A/V Performance - Ars Electronica / Linz

Abysmal means bottomless; resembling an abyss in depth; unfathomable.

Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.

FOLLOW US

We are invited to Ars Electronica 2017

Abysmal - Ars Electronica

Abysmal means bottomless; resembling an abyss in depth; unfathomable.

Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.