Motion Detection using Python and OpenCV

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Jones Granatyr,IA Expert Academy,Dalton Luiz Vargas

5:08:34

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1 - Introduction

1 - Course content.mp4

07:06

2 - Course materials.html

2 - Background subtraction

3 - Background subtraction intuition.mp4

14:08

4 - Temporal median filter intuition.mp4

17:07

5 - Installing Anaconda and PyCharm.mp4

03:30

6 - Temporal median filter implementation 1.mp4

20:15

7 - Temporal median filter implementation 2.mp4

09:20

8 - Temporal median filter implementation 3.mp4

15:24

9 - Other algorithms MOG GMC KNN and CNT.mp4

15:31

10 - Additional reading.html

11 - Image preprocessing techniques.mp4

13:12

12 - MOG GMC KNN and CNT implementation 1.mp4

08:21

13 - MOG GMC KNN and CNT implementation 2.mp4

06:34

14 - MOG GMC KNN and CNT implementation 3.mp4

11:41

15 - MOG GMC KNN and CNT implementation 4.mp4

08:38

16 - MOG GMC KNN and CNT implementation 5.mp4

16:45

17 - Quality comparison 1.mp4

15:56

18 - Quality comparison 2.mp4

06:37

19 - Performance comparison.mp4

05:30

3 - Practical projects

20 - Motion detection 1.mp4

10:30

21 - Edge detection intuition.mp4

05:41

22 - Motion detection 2.mp4

12:40

23 - Social distancing.mp4

16:37

24 - Vehicle counter 1.mp4

12:42

25 - Vehicle counter 2.mp4

10:13

26 - Vehicle counter 3.mp4

14:57

27 - Vehicle counter 4.mp4

15:07

28 - Vehicle counter 5.mp4

12:35

4 - Final remarks

29 - Final remarks.mp4

01:57

Description

Implement a vehicle counter and a social distancing detector using background subtraction algorithms! All step by step

What You'll Learn?

Understand the basic intuition about background subtraction applied to motion detection
Implement MOG, GMG, KNN and CNT algorithms using OpenCV, as well as compare their quality and performance
Improve the quality of the results using pre-processing techniques such as morphological operations and blurring
Implement a motion detector for monitoring environments
Implement a social distancing detector
Implement a car and truck counter using highway videos

Who is this for?

People interested in implementing motion detectors or object counters

Undergraduate and postgraduate students studying Computer Graphics, Digital Image Processing or Artificial Intelligence

Data Scientists who want to increase their knowledge in Computer Vision

More details

Description
Motion detection is a sub-area of Computer Vision that aims to identify motion in videos or in real time. This type of application can be very useful, especially for security systems, in which it is necessary to detect suspicious movements such as a thief trying to enter the house. There are several other applications, such as: traffic analysis on highways, people detection/counting, animal tracking, cyclist counting, among others. A traffic control system can use these techniques to identify the number of cars and trucks that pass through the highway daily and at certain times, so then it is possible to carry out a road maintenance plan.
In this course you will learn in practice how to use background subtraction algorithms to detect movements in videos, all step by step and using Python programming language! Check out the main topics you are going to learn, as well as the hands-on projects:
Basic theoretical intuition about the following background subtraction algorithms: Temporal Median Filter, MOG (Mixture of Gaussians), GMG (Godbehere, Matsukawa and Goldbert), KNN (K Nearest Neighbors) and CNT (Count)
Comparison of quality and performance of each algorithm
Practical project 1: motion detector to monitor environments
Practical project 2: social distancing detector to identify possible crowds of people
Practical project 3: car and truck counter on highways
At the end of the course, you will be able to create your own motion detection projects!
Who this course is for:
People interested in implementing motion detectors or object counters
Undergraduate and postgraduate students studying Computer Graphics, Digital Image Processing or Artificial Intelligence
Data Scientists who want to increase their knowledge in Computer Vision

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Olá! Meu nome é Jones Granatyr e já trabalho em torno de 10 anos com Inteligência Artificial (IA), inclusive fiz o meu mestrado e doutorado nessa área. Atualmente sou professor, pesquisador e fundador do portal IA Expert, um site com conteúdo específico sobre Inteligência Artificial. Desde que iniciei na Udemy criei vários cursos sobre diversos assuntos de IA, como por exemplo: Deep Learning, Machine Learning, Data Science, Redes Neurais Artificiais, Algoritmos Genéticos, Detecção e Reconhecimento Facial, Algoritmos de Busca, Mineração de Textos, Buscas em Textos, Mineração de Regras de Associação, Sistemas Especialistas e Sistemas de Recomendação. Os cursos são abordados em diversas linguagens de programação (Python, R e Java) e com várias ferramentas/tecnologias (tensorflow, keras, pandas, sklearn, opencv, dlib, weka, nltk, por exemplo). Meu principal objetivo é desmistificar a área de IA e ajudar profissionais de TI a entenderem como essa tecnologia pode ser utilizada na prática e que possam visualizar novas oportunidades de negócios.

IA Expert Academy

Instructor's Courses

A plataforma IA Expert tem o objetivo de trazer cursos teóricos e práticos de fácil entendimento sobre sobre Inteligência Artificial e Ciência de Dados, para que profissionais de todas as áreas consigam entender e aplicar os benefícios que a IA pode trazer para seus negócios, bem como apresentar todas as oportunidades que essa área pode trazer para profissionais de tecnologia da informação. Também trazemos notícias atualizadas semanais sobre a área em nosso portal.

Dalton Luiz Vargas

Instructor's Courses

Olá, meu nome é Dalton Luiz Vargas, sou graduado em Ciência da Computação pela Universidade do Contestado (UnC) de Santa Catarina, instrutor no portal IA Expert, um site com conteúdo e cursos teóricos e práticos sobre Inteligência Artificial e instrutor na plataforma EAD Udemy. Trabalho em pesquisas relacionadas à Inteligência Artificial, Aprendizagem de Máquina, Visão Computacional e Métodos de Auxílio à Tomada de Decisão. Sou programador a mais de 6 anos em várias linguagens de programação, especialmente em Python devido a sua praticidade e simplicidade. Meu objetivo como instrutor é ajudar as pessoas a atingirem os seus objetivos e resolver os seus problemas utilizando a computação, contribuindo assim com o aprendizado e crescimento intelectual de cada um.

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