Algorithm for determining whether a point is inside a 3D mesh?

Ray Triangle Intersection appears to be a good algorithm when it comes to accuracy as per this discussion The Wiki has some more algorithms. I am linking it here, but you might have seen this already Can you, perhaps improvise by, maintaining a matrix of relationship between the points and the plane to which they make the vertices? This subject appears to be a topic of investigation in the academia.

Not sure how to access more discussions related to this.

Ray Triangle Intersection appears to be a good algorithm when it comes to accuracy as per this discussion. The Wiki has some more algorithms. I am linking it here, but you might have seen this already.

Can you, perhaps improvise by, maintaining a matrix of relationship between the points and the plane to which they make the vertices? This subject appears to be a topic of investigation in the academia. Not sure how to access more discussions related to this.

This is algorithm is efficient only if you have many queries to justify the time for constructing the data structure. Divide the space into cubes of equal size (we'll figure out the size later). For each cube know which triangles has at least a point in it.

Discard the cubes that don't contain anything. Do a ray casting algorithm as presented on wikipedia, but instead o testing if the line intersects each triangle, get all the cubes that intersect with the line, and then do ray casting only with the triangles in these cubes. Watch out not to test the same triangle more than one time because it is present in two cubes.

Finding the proper cube size is tricky, it shouldn't be neither to big or too small. It can only be found by trial and error. Let's say number of cubes is c and number of triangles is t.

The mean number of triangles in a cube is t/c k is mean number of cubes that intersect the ray line-cube intersections + line-triangle intersection in those cubes has to be minimal c+k*t/c=minimal => c=sqrt(t*k) You'll have to test out values for the size of the cubes until c=sqrt(t*k) is true A good starting guess for the size of the cube would be sqrt(mesh width) To have some perspective, for 1M triangles you'll test on the order of 1k intersections.

I solved my own problem. Basically, I take an arbitrary 2D projection (throw out one of the coordinates), and hash the AABBs (Axis Aligned Bounding Boxes) of the triangles to a 2D array. (A set of 3D cubes as mentioned by titus is overkill, as it only gives you a constant factor speedup.) Use the 2D array and the 2D projection of the point you are testing to get a small set of triangles, which you do a 3D ray/triangle intersection test on (see Intersections of Rays, Segments, Planes and Triangles in 3D) and count the number of triangles the ray intersection where the z-coordinate (the coordinate thrown out) is greater than the z-coordinate of the point.

An even number of intersections means it is outside the mesh. An odd number of intersections means it is inside the mesh. This method is not only fast, but very easy to implement (which is exactly what I was looking for).

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