Efforts are going in the direction of bringing native support for Microsoft’s Kinect v2 to vl, ie making it usable also in vvvv gamma.

We’re assuming that the set of nodes for Kinect2 by @vux available for vvvv beta now is the desired goal.

The purpose of this WIP is to open a discussion which enables future users of this library to bring their thoughts, usecases, ideas and previous experiences forth to be taken into account during this development process.

If we don’t hear from you, here is the set of nodes that we’ll initially be concentrating on:

  • Kinect2: Represents the kinect device. Allows for general configuration for the device and the information it provides

  • RGB (Image): Color camera image

  • Depth (Image): Depth sensor data as an 16-bit image

  • IR (Image): Infrared camera image

  • DepthToRGB (Image): UV map matching depth to RGB

  • RGBToDepth (Image): UV map matching RGB to depth

  • Skeleton: Returns skeleton data for each tracked user

  • BodyIndex(Image): Returns colored version of player (body index image)

  • CameraIntrinsics: Provides FocalLength, PrincipalPoint and RadialDistortion information for the provided Camera Intrinsics

If you have any ideas, comments or in general anything to add to this, please do.

Github repository:

Update: (May 14 29019)

The nodes are now available in a nuget package, to install follow the instructions on github.


I’ve used the faceHD tracking before, and the fusion looked interesting but never used for more than a look, maybe that would be interesting with more access to the pipeline (not even sure thats in the recent versions or not?)


@catweasel interesting point, both of those features are packed up in a single node (each) in DX11, but maybe splitting them into a few more nodes allowing more configuration and control would be a good idea. Do you have any suggestions in particular?


Quick teaser of the current state:

You can already follow the instructions in the github repository and try it out yourself.

Nuget package coming soon.


Great work Randall!