Explore the potential of deep learning techniques in computer vision applications using the Python ecosystem, and build real-time systems for detecting human behavior
Key Features
- Understand OpenCV and select the right algorithm to solve real-world problems
- Discover techniques for image and video processing
- Learn how to apply face recognition in videos to automatically extract key information
Book Description
Computer Vision (CV) has become an important aspect of AI technology. From driverless cars to medical diagnostics and monitoring the health of crops to fraud detection in banking, computer vision is used across all domains to automate tasks. The Computer Vision Workshop will help you understand how computers master the art of processing digital images and videos to mimic human activities.
Starting with an introduction to the OpenCV library, you'll learn how to write your first script using basic image processing operations. You'll then get to grips with essential image and video processing techniques such as histograms, contours, and face processing. As you progress, you'll become familiar with advanced computer vision and deep learning concepts, such as object detection, tracking, and recognition, and finally shift your focus from 2D to 3D visualization. This CV course will enable you to experiment with camera calibration and explore both passive and active canonical 3D reconstruction methods.
By the end of this book, you'll have developed the practical skills necessary for building powerful applications to solve computer vision problems.
What you will learn
- Access and manipulate pixels in OpenCV using BGR and grayscale images
- Create histograms to better understand image content
- Use contours for shape analysis, object detection, and recognition
- Track objects in videos using a variety of trackers available in OpenCV
- Discover how to apply face recognition tasks using computer vision techniques
- Visualize 3D objects in point clouds and polygon meshes using Open3D
Who this book is for
If you are a researcher, developer, or data scientist looking to automate everyday tasks using computer vision, this workshop is for you. A basic understanding of Python and deep learning will help you to get the most out of this workshop.
Table of Contents
- Basics of Image Processing
- Common Operations When Working with Images
- Working with Histograms
- Working with Contours
- Face Processing in Image and Video
- Object Tracking
- Object Detection and Face Recognition
- OpenVINO with OpenCV
Hafsa Asad graduated in Mechatronics Engineering from NUST, Pakistan. She worked at EVEATI Pvt Ltd for 5 years as a Machine Learning Engineer and Trainer.
Vishwesh Ravi Shrimali graduated from BITS Pilani, where he studied mechanical engineering. Since then he has been working with BigVision LLC in deep learning and computer vision and is also involved in creating official OpenCV courses. He has a keen interest in programming and AI and has applied that interest in mechanical engineering projects. He has also written multiple blogs on OpenCV, deep learning on LearnOpenCV, and on computer vision. When he is not writing blogs or working on projects, he likes to go on long walks or play his acoustic guitar.
Nikhil Singh is a computer vision and natural language processing engineer who likes to apply his knowledge of machine learning and deep learning to solve intriguing problems. He currently works as a data scientist for Alixpartners, London. After getting satisfactory results, he believes his work will help Alixpartners to achieve more excellence in their field. He is also the prime author of the book "Video Analytics using TensorFlow" for Apress Publication.
