New AI: This Is A Gaming Revolution!
Summary
TLDRThis 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
🕹️ 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.
Mindmap
Keywords
💡Embodied avatars
💡Real-time motion capture
💡Upper and lower body motion fusion
💡Predictive algorithms
💡Natural movement
💡Body type generalization
💡Joystick control
💡Finger movement accuracy
💡Motion capture data
💡AI technique
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.
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