h1. RGBD (Color data with depth processing)

*_This page discusses what utilities OpenCV should have for handling dense depth data_*

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h3. Input * Fast normals calculation. Ethan has this, completely real time even on a CPU
* convert a uint16 Kinect depth image to the float version (divide by 1000 and replace 0/max to NaN)
* go from a depth image to a structured set of points using K (deals with mask and OutputArray). We have code for that in ecto_opencv

h3. Geometry
* Fast normals calculation. Ethan has this, completely real time even on a CPU
* Compute *R,t*, Rodriques, Quarternion to rotate one vector in 3D so that all points in one scene may be rotated to another.
** All these forms should be easily convertible from/to each other.

h3. Applications
* Plane segmentation. Kurt on this.
* Template on surface
** First, just take a 2D template and project what it would look like on a surface in a scene, assuming that place of projection is planar
*** This is to perspectively warp, say, templates for correlation based mapping
*** Next, map the template to the actual surface
** warp a 3d scene from one view point to another as done by Maria
* Compute *R,t*, Rodriques, Quarternion to rotate one vector in 3D so that all points in one scene may be rotated to another.
** All these forms should be easily convertible from/to each other.

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[[New_functionality_discussion]]