New AI: This Is A Gaming Revolution!

Summary

This video explores the innovative concept of embodied avatars in gaming, where players control their in-game characters using their own body movements without a controller. The technology predicts and fuses upper and lower body motions in real-time, even without lower body sensor data. It adapts to various body types, allows for natural movement paths, and can be controlled via a joystick for comfort. The key to this breakthrough is just 3 hours of motion capture data.

Takeaways

• 🎮 The paper discusses embodied avatars in gaming, where players control their virtual characters with their own body movements instead of a controller.
• 🤔 The concept of embodied avatars was previously challenging due to issues like delay, inaccurate motion mapping, and lack of lower body information.
• 🔮 The new technique predicts future motion based on current movements, making the avatar more responsive and realistic.
• 🧠 It also infers the lower body motion from the upper body motion, fusing them together to create a cohesive virtual character.
• 👀 The technology is not always perfect, as there can be some uncertainty in the motion, but it works well enough for gaming purposes.
• 🛣️ The technique can follow a prescribed path more naturally than previous methods, making movements appear less wooden.
• 🤸‍♂️ The method is versatile and can accommodate different body types and a wide range of movements, such as sitting down or playing baseball.
• 🕹️ If space is limited or players prefer a more relaxed gaming experience, the AI can also provide direct control of the lower body through a joystick.
• 🐰 The technology ensures that fingers in the game move correctly and do not collide, allowing for nuanced interactions like petting a bunny.
• 🌟 The only requirement for this technology to work is 3 hours of motion capture data, after which the AI can perform its advanced motion mapping.
• 🔍 The source code and a playable demo are available for those interested in exploring this technology further.

Q & A

What is the main topic discussed in the 'Two Minute Papers' video transcript?

The main topic is the advancement in embodied avatars technology for gaming, allowing players to control their in-game characters using their own body movements without a controller.

What challenges did previous techniques face in creating embodied avatars for gaming?

Previous techniques faced challenges such as delayed motion, lack of understanding for practical game environments, and the inability to map sensor readings effectively into real human motion in real time.

How does the new technique address the lack of lower body information in the avatar's motion?

The new technique predicts the lower body motion based on the current upper body motion and fuses it with the actual upper body motion to create a more responsive and realistic avatar movement.

What is the significance of the AI's ability to guess the lower body motion from the upper body motion?

This ability is significant as it allows for a more immersive and realistic gaming experience, making the avatar's movements more natural and responsive, even without direct lower body sensor input.

How does the new technique improve upon the movement path following of previous methods?

The new technique allows for more natural and fluid movement paths, making the avatar's motion less wooden and more lifelike, enhancing the gaming experience.

What is the importance of the technique's ability to generalize to different body types?

Generalizing to different body types ensures that the technology is inclusive and can accommodate a wide range of players, making the gaming experience more accessible.

What additional control options does the new technique offer for players with limited space or those who prefer a more comfortable gaming experience?

The technique offers the option to control the lower body directly through a joystick, allowing for 'comfy gaming' and accommodating players with limited space.

How does the technology ensure that the avatar's fingers move correctly in the game without collisions?

The AI technique is designed to analyze and mimic the natural movement of human fingers, ensuring that they move correctly and avoid collisions within the game environment.

What is the only ingredient required to make this technology work, according to the transcript?

The only ingredient required is 3 hours of motion capture data, which the AI uses to learn and mimic human movements effectively.

What additional resources are provided for those interested in the technology discussed in the video?

The video description includes source code and a playable demo, allowing viewers to explore and experience the technology firsthand.

What is the host's perspective on the future of gaming with this technology?

The host is excited about the potential of this technology in future games, expressing enthusiasm and anticipation for the new possibilities it opens up for gaming experiences.

Outlines

00:00

🕹️ Embodied Avatars Revolutionize Gaming

The script introduces a groundbreaking concept in gaming where players can control their in-game avatars using their actual body movements, without the need for a controller. This technology, which seems almost impossible, is made possible by advanced AI algorithms that map sensor readings from a headset and controllers to human motion in real time. The script discusses the challenges of previous techniques, such as delays and inaccuracies in movement mapping, and how the new method overcomes these by predicting and fusing upper and lower body motions. The AI's ability to generalize to different body types and handle complex movements is highlighted, along with the option for direct control of the lower body through a joystick for more comfortable gaming. The script concludes with the impressive capability of the AI to ensure correct finger movements in the game, and the requirement of only 3 hours of motion capture data to train the AI, making it a significant advancement in gaming technology.

Keywords

💡Embodied avatars

Embodied avatars refer to virtual representations of users that mirror their physical movements in real-time within a video game. This concept is central to the video, highlighting a revolutionary approach where players control avatars using their own body movements instead of traditional controllers. This allows for a more immersive gaming experience, as illustrated by examples like using lightsabers or shooting in a game by moving one's body.

💡Real-time motion capture

Real-time motion capture involves recording and translating a person's movements instantaneously into a digital format. This is crucial for creating the embodied avatars discussed in the video. The technology ensures that the virtual character's actions closely match the user's physical movements, addressing previous challenges like delays and inaccurate movement mapping.

💡Upper and lower body motion fusion

Upper and lower body motion fusion is the technique of combining movements from both the upper and lower parts of the body to create a coherent virtual action. The video explains that the AI can predict lower body movements based on upper body actions, making the virtual representation more accurate and responsive. This fusion is essential for realistic avatar motion in gaming.

💡Predictive algorithms

Predictive algorithms are used to anticipate future movements based on current motion data. In the context of the video, these algorithms help the AI guess what the user's lower body will do next, enhancing the responsiveness and accuracy of the embodied avatars. This capability is demonstrated when the AI correctly predicts knee movements based on hand actions.

💡Natural movement

Natural movement refers to the lifelike and fluid motions of avatars as opposed to robotic or stiff movements. The new technique showcased in the video significantly improves the naturalness of avatar movements, making them appear more realistic and human-like. This is important for maintaining immersion in the game environment.

💡Body type generalization

Body type generalization is the ability of the AI to adapt its motion capture techniques to different human physiques. The video highlights this as a non-trivial advancement, ensuring that avatars can realistically mimic a wide variety of body shapes and sizes. This inclusivity enhances the accessibility and realism of the gaming experience.

💡Joystick control

Joystick control allows users to manipulate certain aspects of the avatar's movements using a joystick. This feature is particularly useful in confined spaces or for users who prefer not to move around extensively. The video mentions this as an option for 'comfy gaming,' adding flexibility to the immersive experience.

💡Finger movement accuracy

Finger movement accuracy is the precise tracking and replication of finger movements in the virtual world. The video notes that the AI can ensure fingers move correctly and don't collide, enabling detailed interactions like petting a virtual bunny. This precision is crucial for tasks requiring fine motor skills within the game.

💡Motion capture data

Motion capture data is the recorded movements of real humans, used to train the AI in replicating those movements in avatars. The video states that three hours of such data are sufficient for the AI to achieve its high level of accuracy. This data serves as the foundation for the AI's ability to generate lifelike movements.

💡AI technique

The AI technique refers to the specific artificial intelligence methods employed to achieve the described advancements in avatar movement and realism. The video praises the technique for its ability to generalize movements, predict actions, and provide accurate real-time tracking, marking a significant improvement over previous methods.

Highlights

This paper introduces embodied avatars, allowing users to control video game characters with their own body movements instead of a controller.

The technology enables users to move around in a virtual environment and interact using their body, such as using lightsabers or aiming and shooting.

The system can predict and map sensor readings from a headset and controllers to real human motion in real time.

The system lacks access to lower body information but can guess the lower body's motion based on the upper body's motion.

The system uses motion prediction to make the avatar more responsive and to guess the lower body's motion from the upper body's motion.

The technology can fuse upper and lower body motion together to create a more natural and realistic avatar movement.

The system shows some uncertainty and imperfections in motion prediction, but it still works well in games.

The new technique allows for more natural movement compared to previous methods, making the avatar's path more fluid.

The method can generalize to different body types, making it adaptable for various users.

Users can perform complex movements such as sitting down or playing baseball in the virtual environment.

The AI can provide direct control of the lower body through a joystick for users with limited space or those who prefer a more relaxed gaming experience.

The technology ensures that the avatar's fingers move correctly and do not collide in the game, enhancing the realism of interactions.

Three hours of motion capture data is required for the AI to learn and perform the motion mapping accurately.

The paper includes source code and a playable demo, allowing others to explore and experiment with the technology.

The technology has the potential to revolutionize gaming by enabling more immersive and interactive experiences.

The paper invites scholars and the public to discuss and explore potential applications and uses for this technology.

Transcripts

Now this paper is next level for gaming. It  is about embodied avatars. What is that? Well,  

it is you, not with a controller, but actually  you yourself with your own body within a video  

game. You can move around in an intergalactic  something, use your lightsabers to defeat these  

evil bunny boxes, or aim and shoot in a video  game, but once again, not with a controller,  

but by moving your body. Absolutely  amazing. So, is this really coming?  

Is this even possible? I’ll give you a hint:  this should be absolutely impossible. Why?

Dear Fellow Scholars, this is Two Minute  Papers with Dr. Károly Zsolnai-Fehér.

Well, previous techniques were not so  good at this. They make your virtual  

character move in ways that you did not  move in, suffer from a bit of a delay,  

or they simply don’t understand the kinds of  movement for a practical game environment.  

After all, this task is about mapping the  sensor reading with a headset and a couple  

of controllers into real human motion  and of course, all this in real time.

Now, wait wait wait. We got to talk about  this. Look. This also means that we don’t  

have any access to lower body information,  so all this should be impossible. How does  

it know what the lower body is doing here?  Well, first, it guesses from your motion now  

what your motion might look like in the next few  moments, this makes it more responsive and then,  

it also guesses from the upper body motion  what the lower body should be doing. Then,  

fuse the lower and upper body motion  together. Wow. That is absolute insanity,  

and I did not think that was possible at all. And  yet, look at that footage. If you look closely,  

you see that as the hand moves down here, we can  actually guess what the knees are supposed to be  

doing to achieve this upper body motion. If you  look here, you see that there is some uncertainty,  

it is not always perfect. This also works  in games really well, the lower body here  

does not look exactly the same as in reality,  but there is some correlation between the two,  

one can be guessed from the other with a  reasonable chance of success. Beautiful.

But it gets even more difficult.  Previous techniques are also not  

that great at following a prescribed path,  the movements were a little too wooden. And  

let’s have a look at this new technique, oh  my, that is so much more natural. Loving it.

The new method also generalizes to different  body types, which is not trivial at all,  

and we can also get crazy with the movements,  sit down, play baseball, and so much more.

And get this, if we don’t have too much space  around us, or let’s be honest, we are a bit lazy,  

and this AI technique is also ready to  give us direct control of the lower body  

through a joystick, and that means…  oh yes. Comfy gaming. Loving it.

Now hold on to your papers Fellow Scholars,  

because it can even make sure that our fingers  are moving correctly in the game, and that they  

don’t collide. You can even pet a bunny in  a virtual world, or be fabulous like this.

And we only need one more  ingredient to make all this happen.  

So, what is the only ingredient that  remains? Well, 3 hours of motion capture  

data. Yes. The AI looks at 3 hours of human  movement, and if you add this algorithm,  

it is able to perform this absolute  miracle. An absolute slam dunk paper. Wow.

Make sure to check it out in the video  description. Source code and a playable  

demo is also included. So good,  loving it. I cannot wait to see  

this in the games of the future.  What a time to be alive! Also,  

what do you Fellow Scholars think? What would you  use this for? Let me know in the comments below.