I will in this post write down an explanation of the intuition behind the paper 'As-Rigid-As-Possible Surface Modeling'.

The paper describes a mesh deformation technique called ARAP(As-Rigid-As-Possible) that allows you to change the shape of a mesh, while still preserving its detail. This means the details of mesh doesn't get stretched, get flattened, nor get sheared. In the animation above, I am using the ARAP implementation from libigl to deform the armadillo mesh. We can see in the animation that the details of the armadillo are preserved even when it is deformed; the shape of the eyes and teeth stay the same, and the bumpy pattern on the arms and legs stay the same, and this makes the deformation appear natural.

The technique allows a user to deform a mesh like this: we specify a couple of vertices on the original mesh. Now we modify the positions of these vertices, and the result of this, is that the rest of the vertices of the mesh will naturally adapt to this. In the animation, we have specified five vertices, which can be seen below:

The vertices at the hands and nose are moved, while the vertices at the legs are kept static. If we move the vertices at the hands and nose, we get the animation seen above. The purpose of the vertices at the legs are to anchor the armadillo, so that the legs stay still, even when the three vertices are moved.

How can we implement such a deformation technique, that allows the user to modify the mesh while still preserving the detail? We will now explain how the ARAP technique from the paper works. Let us look at a single edge of the undeformed mesh, with the vertices $\mathbf{p}_i$ and $\mathbf{p}_j$. It will be deformed into the vertices $\mathbf{p}_i'$ and $\mathbf{p}_j'$. Now, we want the original geometric detail of the mesh to be preserved as well as possible, after the deformation. The paper aims to achieve this, by ensuring that the vertices are deformed as rigidly as possible; that is, they are deformed by a rigid body transform. Such a transform contains no scaling, nor shearing, which is exactly what we want. To accomplish this, we impose a condition on the deformed vertices: \begin{equation} \mathbf{p}_i' - \mathbf{p}_j' = \mathbf{p}_i - \mathbf{p}_j \label{eq:condone} \end{equation} This condition basically means that every deformed edge should maintain its original length and direction. See the below image for an example of this:

As can be observed, the deformed edge $(\mathbf{p}_i',\mathbf{p}_j')$ is just the undeformed edge $(\mathbf{p}_i,\mathbf{p}_j)$, but translated to the right a bit. Under this condition, translation is allowed, as long as scaling is not introduced. Note that condition $\eqref{eq:condone}$ is not maintained in the below case

Since now scaling has been introduced to the deformed edge, and it has thus become longer. So the condition makes sure that scaling and shearing can not be introduced, which is exactly what we want. But an issue with our current condition, is that the direction of the deformed edge must match the direction of the original edge. This means that our deformation can not perform any rotation, which is too restrictive. In the animation shown earlier, there is clearly a rotation component to the animation, for instance when the arm is being moved up and down. We will fix this by making our condition less restrictive: \begin{equation} \mathbf{p}_i' - \mathbf{p}_j' = \mathbf{R}_i(\mathbf{p}_i - \mathbf{p}_j) \label{eq:condtwo} \end{equation} we have introduced a rotation matrix $\mathbf{R}_i$ to our condition. This matrix encodes the fact that our original edge can be rotated when deformed. Rotated by some arbitrary rotation matrix $\mathbf{R}_i$. So now the below deformation is now possible:

Shearing and scaling is still not possible, since the length must still be preserved by the condition. Furthermore, a proper rotation matrix can not introduce any scaling nor shearing, so even if we introduce $\mathbf{R}_i$, scaling can not be introduced. To summarize. The condition ensures that the edges can only be transformed by a translation and rotation transform (which is precisely a rigid transform)Now, here is how we will implement our deformation algorithm: when doing the deformation, we will ensure that the condition $\eqref{eq:condtwo}$ is maintained as well as possible, for all the edges on the mesh. In practice, it is not possible to exactly fulfill the condition for all edges, but we will make sure that it is at least fulfilled in a least-squares sense. So for all edges, we want to ensure that the quantity \begin{equation} w_{ij} ||(\mathbf{p}_i' - \mathbf{p}_j') - \mathbf{R}_i(\mathbf{p}_i - \mathbf{p}_j) ||^2 \label{eq:ls} \end{equation} is as minimal as possible($w_{ij}$ is a weighting factor, that we will discuss in more detail later). If this quantity is minimal, then the edge will have been transformed by a transform that is As-Rigid-As-Possible, which is the main idea of the paper. Every edge in the mesh, has a corresponding term of the form $\eqref{eq:ls}$. In the paper, the authors compute the sum of all these terms, and denote this sum as $E(S')$: \[ E(S') = \sum_{i=1}^n w_i \sum_{j \in N(i)} w_{ij} ||(\mathbf{p}_i' - \mathbf{p}_j') - \mathbf{R}_i(\mathbf{p}_i - \mathbf{p}_j) ||^2 \] This is equation (7) from the paper. Now, if this sum is minimal, then all edges will be transformed As-Rigid-As-Possible(ARAP).

In order to compute the deformed mesh, we need to find the values of the deformed vertices $\mathbf{p}_i'$ that minimize $E(S')$. We will let the user manipulate a couple of vertices freely, let's call them $\mathbf{p}_a'$ and $\mathbf{p}_b'$ (these could be the vertices on the hands of the armadillo). For these vertices, we already know their values, since they are specified by the user. But for the remaining vertices, we must set them to values that minimize the sum $E(S')$, because then the deformation is ARAP. Also note that $\mathbf{p}_i$ represents the undeformed vertices, and we already know the values of them too.

However, we also don't know the values of the introduced rotation matrices $\mathbf{R}_i$. So, we need to solve for both $\mathbf{p}_i'$ and $\mathbf{R}_i$ in order to find the deformed positions, since the values of $\mathbf{p}_i'$ clearly depends on the values of $\mathbf{R}_i$. Solving for both at once is complicated, so the authors employ an Alternating Minimization scheme.

The authors solve the problem as follows: they guess some initial values for $\mathbf{R_i}$ and $\mathbf{p_i'}$. Then, they assume that their guess for $\mathbf{p_i'}$ is correct, and from this assumption, they find values of $\mathbf{R_i}$ that are ARAP(using equation (6) from the paper). Then, they assume their obtained values for $\mathbf{R_i'}$ is the correct solution, and then find values for $\mathbf{p_i}$ that are ARAP(by solving equation (9) in the paper). If you repeat this procedure a number of iterations, you will arrive at a satisfactory solution. This kind of strategy is called Alternating Minimization, and you can read more about this topic in Section 12.3 of this book.

Finally, we will give a brief explanation for the weight factor $w_{ij}$, that we did not explain earlier. Low-quality triangle tessellations may cause issues when deforming a mesh. Consider for instance the below mesh

There are quite a few diagonal edges, running from top-left to bottom-right, so this tessellation is a bit uneven This kind of tessellation causes issues when using ARAP, as can be seen in figure 2 of the original paper. It results in an asymmetric deformation, which is not desirable. The issue is fixed by using a cotangent weighting factor: \[ w_{ij} = \frac{1}{2}(\cot \alpha + \cot \beta) \] Where $\alpha$ and $\beta$ are the two angles opposite to the edge, as illustrated in the image below

The cotangent weight gives a lower weight to the diagonal edges of the tessellation (since $\alpha$ and $\beta$ have higher values for these edges). This means that they have less effect on the final deformed mesh, and this removes the asymmetric artifact.