Novel Convolution Kernels for Computer Vision and Shape Analysis based on Electromagnetism

06/20/2018
by   Dominique Beaini, et al.
0

Computer vision is a growing field with a lot of new applications in automation and robotics, since it allows the analysis of images and shapes for the generation of numerical or analytical information. One of the most used method of information extraction is image filtering through convolution kernels, with each kernel specialized for specific applications. The objective of this paper is to present a novel convolution kernels, based on principles of electromagnetic potentials and fields, for a general use in computer vision and to demonstrate its usage for shape and stroke analysis. Such filtering possesses unique geometrical properties that can be interpreted using well understood physics theorems. Therefore, this paper focuses on the development of the electromagnetic kernels and on their application on images for shape and stroke analysis. It also presents several interesting features of electromagnetic kernels, such as resolution, size and orientation independence, robustness to noise and deformation, long distance stroke interaction and ability to work with 3D images

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 10

page 11

page 12

page 14

page 15

page 18

page 20

page 23

04/18/2020

Adaptive Attention Span in Computer Vision

Recent developments in Transformers for language modeling have opened ne...
12/25/2020

Kernel-Independent Sum-of-Exponentials with Application to Convolution Quadrature

We propose an accurate algorithm for a novel sum-of-exponentials (SOE) a...
06/05/2018

Deep Gaussian Processes with Convolutional Kernels

Deep Gaussian processes (DGPs) provide a Bayesian non-parametric alterna...
08/20/2021

Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions

This paper proposes a novel deep learning approach for single image defo...
11/30/2021

DiffSDFSim: Differentiable Rigid-Body Dynamics With Implicit Shapes

Differentiable physics is a powerful tool in computer vision and robotic...
12/19/2019

Tangent Images for Mitigating Spherical Distortion

In this work, we propose "tangent images," a spherical image representat...
07/22/2013

A Novel Equation based Classifier for Detecting Human in Images

Shape based classification is one of the most challenging tasks in the f...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.