We were discussing Signature verification methods. We reviewed the stages involved with Signature verification. Then we also enumerated the feature extraction techniques. After that, we compared online and offline verification techniques. We also discussed the limitations of image processing and the adaptations for video processing.Then we proceeded to discussing image embedding in general.
Today we continue our discussion of Convolutional Neural Network (CNN) in image and object embedding in a shared space.
The purpose of the embedding is to map an image to a point in the embedding space so that it is close to a point attributed to a 3D model of a similar object. A large amount of training data consisting of images synthesized from 3D shapes is used to train the CNN.
In order to play up the latent objects in images, similar objects were often used in dissimilar images. The dissimilarity was based on viewpoint, lighting, background differences, partial hiding and so on. 3D object representations do not suffer from these dissimilarities and are therefore much easier to establish similarity.
Images and 3D shapes share the embedded space. In that space, both can be measured as if their 3D form was directly available. This embedded space is plotted with each object given a co-ordinate comprising of the dimension reduced form of the distances between the underlying shape and the entire set.  This way two neighboring points in the embedded space are likely to represent similar shapes, as they agree to a similar extent, on their similarities with all the other shapes.

#codingexercise
A step array is an array of integer where each element has a difference of atmost k with its neighbor. Given a key x, we need to find the index value of k if multiple element exist return the index of any  occurrence of key.
Input : arr[] = {4, 5, 6, 7, 6}
           k = 1
           x = 6
Output : 2

int GetIndex(List<int> A, int x, int k)
{
int i = 0;
while (i < A.Length)
{
if (A[i] == x)
   return i;
i = i + Math.Max(1, Math.Abs(A[i]-x)/k);
}
return -1;
}