5 Interesting Applications of Machine Learning in Virtual Reality

Learn more about SSN SACE’s PG Program in Business Analytics and Data Science

""
1
Name
Educational Qualificationyour full name
Mobile Number
City
Previous
Next

With many VR systems already in place across domains from entertainment to healthcare-training, Machine Learning (ML) is now creating a transformative effect by:

  • Improving user-interaction to provide a better immersive experience
  • Cutting down the cost of expensive VR systems

Here are a few examples:

1. Gesture Recognition

Most VR systems today use 2D image processing techniques to recognize hand gestures. Earlier gaming consoles (think Nintendo) had similar functionalities, but they were limited to mapping predetermined variants of gestures to specific actions.

Today with ML techniques, we are able to use Convoluted Neural Network’s (CNN) ability to process spatial data, i.e. images, to create a system that recognizes the unique gestures of people irrespective of age, physiology, cultural differences and more.

2. Eyeball Tracking

VR systems simulate natural experiences visually with the help of eyeball tracking sensors. The system understands where the user is looking and applies more processing power and deeper rendering toward that area alone while peripheral views are less visible – much like natural eyesight. However, this is not very cost-effective.

Instead, we can input the user’s head position and movements to a CNN to estimate their gaze, thereby eliminating the necessity for an expensive eyeball tracker.

3. Creating VR in VR

When building a VR system, the first step is to model the environment. This is generally done on a 2D canvas which can be limiting.

What if we told you that with Machine Learning, we could model a VR environment from inside the system? Similar to Google’s Quick Draw’s brain, we can employ a neural network to recognize a user’s doodles from within the VR environment itself.

4. VR Gaming Narrative

Horror games in VR are immersive and can be traumatic to some users. To address this issue, VR developers are working toward developing a system that varies the intensity of the game based on the user’s physical reactions.

With Machine Learning, physical responses such as facial expressions and heart-rate can be measured using head-mounted cameras, Fitbit or other similar devices to provide data to a Reinforcement Learning Algorithm, based on which the intensity of the game can be modified.

5. Illuminating VR Environments

To make computer-generated images look real, transmission of light falling on virtual world characters is key. Animation companies such as Pixar and Disney are moving in this direction to make their movies appear closer to life. This is applicable to VR too. However, since the user interacts dynamically in a VR environment, as opposed to a movie where every frame rendered is pre-planned, this functionality becomes more complex.

Research has shown that using Machine Learning, we can use a back propagation neural network that can be trained with light rays to simplify the process. The resultant neural meshes can easily help achieve a more realistic illumination in VR.

These are just a handful of areas where Machine Learning has impacted Virtual Reality. Just scratching the surface…. Have you come across any other applications?

Check out SSN SACE’s PG Program in Business Analytics & Data Science

Recent Posts

Leave a Comment