Satya Mallick
1. Image Classification vs. Object Detection Image Classification is a problem where we assign a class label to an input image. For example, given an input image of a cat,
Overview OpenCV.org, in partnership with Big Vision LLC (owner of LearnOpenCV.com) has launched a Kickstarter campaign to create 3 Computer Vision courses. There are many benefits of buying these courses
Face Recognition is a computer vision technique which enables a computer to predict the identity of a person from an image. This is a multi-part series on face recognition. This
In today’s post we will describe a class of region filling algorithms called image inpainting. Imagine finding an old family photograph. You scan it and it looks great except for
In this post, we will compare the performance of various Deep Learning inference frameworks on a few computer vision tasks on the CPU. Surprisingly, with one exception, the OpenCV port
In this post, we will show how to use Hu Moments for shape matching. You will learn the following What are image moments? How are image moments calculated? What are
It gives me immense pleasure to announce the best project award for our online course “Computer Vision for Faces” (cv4faces) for this semester. Why do we have a Final Project
In Computer Vision, the term “image segmentation” or simply “segmentation” refers to dividing the image into groups of pixels based on some criteria. A segmentation algorithm takes an image as
In this post, we will cover how to use OpenCV’s multi-object tracking API implemented using the MultiTracker class. We will share code in both C++ and Python. Before we dive
In this post, we will learn about a Deep Learning based object tracking algorithm called GOTURN. The original implementation of GOTURN is in Caffe, but it has been ported to
Ideas in Machine Learning have a “winner takes all” quality. When an idea takes off, it dominates the field so completely that one tends to believe it is the only
In this post, we share some formulas for calculating the sizes of tensors (images) and the number of parameters in a layer in a Convolutional Neural Network (CNN). This post
