How Do You Compute Curvature Indices for a Polyhedron?

In summary, the paper "A Practical Approach for 3D Model Indexing by combining Local and Global Invariants" by Jean-Philippe Vandeborre, Vincent Couillet and Mohamed Daoudi describes a method for computing curvature indices for a polyhedron. This involves fitting a quadratic function to the neighborhood of a face and using the least square method to obtain the principal curvatures as the eigenvalues of the Weingarten endomorphism. The first and second fundamental forms are also used in this process. However, the specifics of applying these concepts may be confusing for those not well-versed in mathematics. Further research may be necessary to fully understand and apply this method.
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Hello. I was wondering if anyone here could help me understand this method I found described in the paper:

"A Practical Approach for 3D Model Indexing by combining Local and Global Invariants" by Jean-Philippe Vandeborre, Vincent Couillet and Mohamed Daoudi

for computing curvature indices for a polyhedron. I'm not very good at mathematics, so please try to dumb down your explanation accordingly, if possible ;)

-> To calculate the principal curvatures associated with a face (wording is mine, not an exact quote):
Fit a quadratic to the neighborhood of a face (the centroid of the face and those of its immediately adjacent faces) using the least square method;
Obtain the principal curvatures (two values, k1 and k2) as the eigenvalues of the Weingarten endomorphism W = I^-1 dot II where I and II are the first and second fundamental forms.

Now, I know what are centroids and eigenvalues, and how to calculate them. I do NOT know, and never used, least squares, Weingarten endomorphisms and fundamental forms, whatever they are. I cannot afford the time or cost of acquiring and learning from a book right now, but a quick wikipedia search returns this:

* Fundamental forms:

"the first fundamental form is the inner product on the tangent space of a surface"
"In differential geometry, the second fundamental form (or shape tensor) is a quadratic form on the tangent plane of a smooth surface"

This leaves me even more confused, and the formulas provided don't really match with my simple notion of inner product where (a,b).(c,d) = ac+bd ...
If anyone could explain this step in a simpler manner (even as a formula I can use in this specific instance), I'd be thankful. I might be able to figure it out if I had any idea of what I'm supposed to obtain as the end result, but I don't.

* Least squares:

"The minimum of the sum of squares is found by setting the gradient to zero. Since the model contains m parameters there are m gradient equations. (...)" etc.

This confuses me the most, since I have no idea of how to apply this to my set of centroids.

* Weingarten endomorphism:

I know it exists, but I can't find any encyclopedic information on it. However if I just have to use the provided formula, that won't be a problem, as long as I figure out the fundamental forms thing.

* Principal curvatures:

Wikipedia has a reasonably informative article on this, which is why I hope someone here will be able to help me. Unfortunately the article doesn't explain how to obtain the values.
 
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In short, I need help understanding the method described in the paper for computing principal curvatures of a polyhedron. I understand the general concept, but I'm not sure how to apply it in practice. Any help is appreciated!
 

FAQ: How Do You Compute Curvature Indices for a Polyhedron?

1. What is the purpose of calculating curvature indices?

The purpose of calculating curvature indices is to measure the degree of curvature or bend in a surface or object. This can be useful in fields such as engineering, geology, and mathematics to analyze and understand the shape and properties of different objects and surfaces.

2. How do you calculate curvature indices?

The most commonly used method for calculating curvature indices is through differential geometry, using equations such as the Gaussian curvature and mean curvature. These equations involve measuring the change in direction or slope of a surface at different points and calculating the curvature at each point.

3. What are some practical applications of curvature indices?

Curvature indices have many practical applications, such as in structural engineering to design and analyze the stability of curved structures, in geology to determine the shape and formation of landforms, and in computer graphics for creating realistic and accurate 3D models.

4. Can curvature indices be negative?

Yes, curvature indices can be negative. Negative curvature occurs when the surface bends inwards, forming a concave shape. This is in contrast to positive curvature, which occurs when the surface bends outwards, forming a convex shape. Both positive and negative curvature indices have important applications in different fields of study.

5. Are there any limitations or assumptions when calculating curvature indices?

One limitation of calculating curvature indices is that it assumes the surface is smooth and continuous, which may not always be the case in real-world scenarios. Additionally, the accuracy of the calculations may be affected by factors such as measurement errors and the resolution of the data used.

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