This page discusses what utilities OpenCV should have for handling dense depth data

• 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
• 3d visualizer

• Fast normals/curvature 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.

• 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

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