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Category: OpenCV

#006 Advanced Computer Vision – Object tracking with Mean-Shift and CAMShift algorithms

19.01.2023

Highlights: In this post, we’re going to talk about the most common object tracking algorithms – Mean-Shift and CAMShift (Continuously Adaptive Mean-Shift). First, we are going to describe the theory behind the Mean-Shift algorithm. Then, we’ll explain how to apply this algorithm for object tracking in OpenCV with Python. Finally, we’ll learn how to extend the Mean-Shift algorithm into a CAMShift algorithm. So, let’s begin. Tutorial Overview: 1. Mean-Shift algorithm – introduction First, let’s explain…
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#007 Advanced Computer Vision – Video Stabilization

19.01.2023

Highlights: Hello and welcome. In this post[1], we will learn to remove unwanted camera movement or shake from a video using a technique called Video stabilization. It is typically used to make videos appear smoother and more professional. There are a variety of techniques that can be used to stabilize a video, including image cropping, image scaling, and frame-by-frame motion estimation. In this post, we will present an efficient and robust implementation of a digital…
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#005 Advanced Computer Vision – Basketball Player Tracking with Open CV

16.01.2023

Highlights: Hello and welcome. In this post, we are going to talk about the concept of object tracking. We will clarify the idea of object tracking and how this concept differs from object detection. After that, we will learn about the most popular object-tracking algorithms from the OpenCV library and we will explore their applications in real-world scenarios. In particular, we are going to learn how to use object tracking to track basketball players on…
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#004 Advanced Computer Vision – YOLO Object Detection

16.01.2023

Highlights. Hello and welcome. In this post, we are going to talk about one of the most popular algorithms for object detection called the Yolo object detection algorithm.  We will cover the basic theory behind YOLO object detection [1], its benefits, and how this algorithm has evolved over the last couple of years. Finally, we will examine some real-life applications of YOLO object detection, more specifically, we will explain how to use YOLO for detecting…
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#002 Advanced Computer Vision – Motion Estimation With Optical Flow

12.10.2021

Highlights: Techniques like Object Detection have enabled computers of today to detect object instances easily. However, tracking the motion of objects such as vehicles across all frames of a video, estimating their velocity, and predicting their motion requires an efficient method such as Optical Flow. In our previous posts, we provided a detailed explanation about two of the most common Optical Flow methods – the Lucas Kanade method and the Horn & Schunck method. In…
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