Sampling hair density field by deterministic Importance Sampling

First, don't tell me how shave works. First, 99% of people use pirated hair. Second, shave, including Houdini fur, do not perfectly solve the precise hair growth problem after high displacement. Houdini fur's paint density is completely a waste based on the difference value after Vertex coloring. It cannot be perfectly combined with 3D paint. The solution I proposed perfectly solves this problem and is especially suitable for the production of plants, turf, and so on. In addition, it can be used together with the Renderer supporting procedural primtive to achieve the same full hair difference as King Kong. Everything is for the most accurate, everything is for the most foolish control.

• Step 1: Paint density texture in mudbox or the others sculpt software. Sorry for my poor artist ability.
• Step 1: Draw the density distribution in the mudbox. Use the geometryimageviewport filter plug-in to render the object coordinate system value and normal value after displaced to the two picture posts. Currently, the mudbox does not provide the baking function for the world.

• Step 2: Export the density field as following. This is an probability density function (PDF for short ).
• Part 2: export the density distribution as the probability distribution function of hair growth.
• Step 3: Applied the classical inversion function and quasi monte carlo sampling, We coshould genereate deterministic amount of the sampler positions.
• Part 3: Use my externalProgramPreview distribution. The sampling point UV is generated using pseudo-random monte carlo sampling. You can use uniform or QMC sequence to adjust the sampling point UV.

• Step 4: I made a Maya DG to generate curves in Maya. The root follicles will be placed on subdivided diplaced surface.
• To achieve hair growth, I also provided an DG node to read the density map line chart generated in the first step for sample and growth.