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Computer Vision by Using C++ and OpenCV
Overview In the rapidly evolving landscape of technology, computer vision stands at the forefront of innovation, enabling machines to interpret …
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Overview
Computer vision plays a pivotal role across various industries, from healthcare and automotive to security and entertainment. Through this course, participants will embark on a structured journey starting with foundational concepts and gradually progressing to more intricate algorithms and applications. The course begins by establishing a solid understanding of image processing fundamentals, including techniques like filtering, edge detection, and geometric transformations. These are essential building blocks for manipulating and enhancing digital images programmatically.
Moving forward, the curriculum delves into the heart of computer vision with topics such as object detection, tracking, and motion analysis. Learners will master techniques to identify and analyze objects within images and video streams, laying the groundwork for creating intelligent systems capable of real-time decision-making based on visual inputs. Moreover, the course covers advanced feature extraction methods like SIFT and SURF, which are indispensable for recognizing and matching distinctive features in images across different scales and orientations.
Practical application is a cornerstone of this course, with hands-on projects designed to reinforce theoretical learning and cultivate proficiency in C++ and OpenCV. By working through these projects, participants will gain practical experience in implementing computer vision algorithms, from building basic image classifiers to developing sophisticated applications such as augmented reality filters or autonomous vehicle navigation systems.
Upon completion, learners will emerge with a comprehensive skill set that includes proficiency in C++ programming, mastery of OpenCV library functionalities, and the ability to tackle complex challenges in computer vision. Whether you are a seasoned programmer aiming to specialize in visual perception technologies or a newcomer curious about the possibilities of image analysis and recognition, this course provides the tools and knowledge to embark on a successful journey in the field of computer vision.
Learning Outcomes
- Understand fundamental concepts in computer vision and image processing.
- Implement image filtering, edge detection, and geometric transformations.
- Develop skills in object detection, tracking, and motion analysis.
- Apply feature extraction techniques such as SIFT and SURF.
- Build hands-on projects to recognize objects and analyze video sequences using C++ and OpenCV.
What Will Make You Stand Out?
On Completion of this online course, you’ll acquire:
- CPD QS Accredited Course.
- Upon Course Completion, Earn a Complimentary PDF and a hard copy Certificate to Showcase Your Enhanced Skills.
- Lifetime access.
- 24x7 Tutor Support.
- Complete the course at your own pace.
Description
This course provides a deep dive into computer vision using C++ and OpenCV, two essential tools for developers and engineers interested in visual perception technologies. Starting with an introduction to image processing techniques, you will learn how to manipulate images programmatically, including filtering, edge detection, and geometric transformations. Moving forward, the course covers advanced topics like object detection, tracking, and motion analysis, crucial for creating intelligent systems that can interpret visual data. You will explore feature extraction methods such as SIFT (Scale-Invariant Feature Transform) and SURF (Speeded Up Robust Features) to identify distinct points in images.
Throughout the course, practical hands-on projects will reinforce your learning, from building a basic object detection system to developing more complex applications like video surveillance or augmented reality filters. By the end, you will have the skills to tackle real-world challenges in computer vision, armed with proficiency in C++ programming and OpenCV libraries.
Who is this course for?
This course is ideal for programmers and developers looking to specialize in computer vision using C++ and OpenCV. It is also suitable for beginners with basic programming knowledge who are interested in learning about image processing and machine vision applications. Professionals in fields such as robotics, AI, autonomous vehicles, and healthcare will find this course instrumental in advancing their careers.
Requirements
Access to a computer with internet connectivity and a desire to learn and succeed in your home-based business venture. No prior experience or qualifications are necessary.
Certification
Upon successful completion of the Computer Vision by Using C++ and OpenCV course, learners can obtain both a PDF certificate and a Hard copy certificate for completely FREE. The Hard copy certificate is available for a nominal fee of £3.99, which covers the delivery charge within the United Kingdom. Additional delivery charges may apply for orders outside the United Kingdom.
Career Path
- Computer Vision Engineer: Develop algorithms for image and video analysis.
- Robotics Software Engineer: Implement vision-based systems for robotic perception.
- AI/Machine Learning Engineer: Integrate computer vision capabilities into AI models.
- Autonomous Vehicle Engineer: Build vision systems for navigation and object recognition.
Course Curriculum
| Unit 01: Set up Necesssary Environments | |||
| Module 01: Driver installation | 00:06:00 | ||
| Module 02: Cuda toolkit installation | 00:01:00 | ||
| Module 03: Compile OpenCV from source with CUDA support part-1 | 00:06:00 | ||
| Module 04: Compile OpenCV from source with CUDA support part-2 | 00:05:00 | ||
| Module 05: Python environment for flownet2-pytorch | 00:09:00 | ||
| Unit 02: Introduction with a few basic examples! | |||
| Module 01: Read camera & files in a folder (C++) | 00:11:00 | ||
| Module 02: Edge detection (C++) | 00:08:00 | ||
| Module 03: Color transformations (C++) | 00:07:00 | ||
| Module 04: Using a trackbar (C++) | 00:06:00 | ||
| Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) | 00:13:00 | ||
| Unit 03: Background segmentation | |||
| Module 01: Background segmentation with MOG (C++) | 00:04:00 | ||
| Module 02: MOG and MOG2 cuda implementation (C++ – CUDA) | 00:03:00 | ||
| Module 03: Special app: Track class | 00:06:00 | ||
| Module 04: Special app: Track bgseg Foreground objects | 00:08:00 | ||
| Unit 04: Object detection with openCV ML module (C++ CUDA) | |||
| Module 01: A simple application to prepare dataset for object detection (C++) | 00:08:00 | ||
| Module 02: Train model with openCV ML module (C++ and CUDA) | 00:13:00 | ||
| Module 03: Object detection with openCV ML module (C++ CUDA) | 00:06:00 | ||
| Unit 05: Optical Flow | |||
| Module 01: Optical flow with Farneback (C++) | 00:08:00 | ||
| Module 02: Optical flow with Farneback (C++ CUDA) | 00:06:00 | ||
| Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA) | 00:05:00 | ||
| Module 04: Optical flow with Nvidia Flownet2 (Python) | 00:05:00 | ||
| Module 05: Performance Comparison | 00:07:00 | ||
Frequently Asked Questions
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
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Number of Units:
22 -
Access:
1 Year -
Duration:
2 hours, 31 minutes -
PDF Certificate
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