Daniel Holden, a researcher from the University of Edinburgh, has recently designed a new system of character control that promises to not only make character movements in video games look more realistic but also to ensure that games run more smoothly in general. Announced in a paper released by the university entitled 'Phase-Functioned Neural Networks for Character Control,' the system uses neural networks in order to give characters a wide range of motion while drawing from a relatively small database.
In games up until now, characters moved by combining series of pre-designed animations stored locally on the game's device or the disc itself. This system is both data heavy and constrained, since the characters can only move in set patterns. Holden's neural network relies on motion data collected from actual footage of a model in motion, trimming from that to invent any independent movement.
What's Driving This Trend
- Motion Data Neural Networks
- Using motion data and neural networks for character control in video games can enhance realism and improve gameplay.
- Real-time Character Animation
- Developing real-time character animation systems using neural networks can revolutionize the gaming industry by providing smoother and more natural movements.
- Database-driven Character Motion
- Implementing database-driven character motion with neural networks can optimize storage and allow for more diverse and dynamic character animations.
Who This Affects Most
- Video Games
- The video game industry can benefit from incorporating motion data neural networks to create more immersive and realistic gaming experiences.
- Artificial Intelligence
- The field of artificial intelligence can explore the application of neural networks in character control as a disruptive innovation for interactive virtual environments.
- Animation and Visual Effects
- Incorporating real-time character animation using neural networks can revolutionize the animation and visual effects industry by streamlining the animation production process.
