Facebook, the mogul of online socializing, tried to bring social experiences to virtual reality by launching
Facebook Spaces a year back. Facebook Spaces is an online gathering of VR enthusiasts wherein one can engage with their friends and family in the form of customizable cartoon-like avatar characters.
In order to enhance the user's social VR experience further, Facebook-owned Oculus is working to improve hand tracking technology. The hope is to allow for more accurate avatars and intuitive controls in virtual reality.
Oculus Hand-Tracking
Maria Fernandez Guajardo, head of product management on core tech, recently offered a glimpse into the ongoing research at Oculus's R&D Division.
During the presentation, Guajardo unveiled a hand-tracking system (based on computer-vision) that incorporates a host of smart technologies such as machine-learning algorithms. She said that this hand-tracking system is “far more accurate than any method before for tracking a single hand, two hands, and hand-object interactions.”
https://www.youtube.com/watch?v=y1DmFKiQCvk
In order to operate with such accuracy, Oculus makes use of a marker-based system that records hand interactions and movements in higher detail. The recorded data is then condensed into 2D imagery, thereby setting up a convolutional neural network. This neural network identifies the positions of markers across a large set of hand imagery which will help the tracking system figure out how the hand should look under different marker position scenarios.
Image: Oculus
Apparently, this trained system can then be fed to the markerless camera input of virtual reality headsets and allow them to track hand-movements based on the information the VR headset cameras have captured.
Results of Oculus' Hand-Tracking Solutions
Image: Oculus
Having tested this system, Oculus claims to have an accuracy rating much higher than its competitors. In the case of single-hand tracking, the company claims to have attained an exemplary success rate of 100% against the 90.49% rate achieved through other hand-tracking methods.
Moreover, the above chart shows that there is a significant jump in the results and accuracy of two-handed tracking and hand-to-object tracking interactions. It seems that as these solutions come to the market in the near future, competitors in this hand-tracking segment, such as Leap Motion, will certainly have a run-for-their-money.
The hand-tracking solution, when implemented, will certainly add a new sense of immersion for touch and feel in the VR Porn games.
