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Shree Nayar

This course focuses on the detection of features and boundaries in images. Feature and boundary detection is a critical preprocessing step for a variety of vision tasks including object detection, object recognition and metrology – the measurement of the physical dimensions and other properties of objects. The course presents a variety of methods for detecting features and boundaries and shows how features extracted from an image can be used to solve important vision tasks.

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This course focuses on the detection of features and boundaries in images. Feature and boundary detection is a critical preprocessing step for a variety of vision tasks including object detection, object recognition and metrology – the measurement of the physical dimensions and other properties of objects. The course presents a variety of methods for detecting features and boundaries and shows how features extracted from an image can be used to solve important vision tasks.

We begin with the detection of simple but important features such as edges and corners. We show that such features can be reliably detected using operators that are based on the first and second derivatives of images. Next, we explore the concept of an “interest point” – a unique and hence useful local appearance in an image. We describe how interest points can be robustly detected using the SIFT detector. Using this detector, we describe an end-to-end solution to the problem of stitching overlapping images of a scene to obtain a wide-angle panorama. Finally, we describe the important problem of finding faces in images and show several applications of face detection.

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What's inside

Syllabus

Getting Started: Features and Boundaries
Edge Detection
Boundary Detection
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SIFT Detector
Image Stitching
Face Detection

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers features and boundaries, which are foundational in computer vision
Taught by Shree Nayar, a recognized researcher in computer vision
Explores feature and boundary detection methods, which are applicable to industry
Provides practical examples such as object detection, face detection, and image stitching
Requires familiarity with image processing, which may be a prerequisite for some learners

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Features and Boundaries with these activities:
Review Image Processing Fundamentals
Refresh your knowledge of the basics of image processing, including concepts like pixels, color channels, and image formats.
Browse courses on Image Processing
Show steps
  • Review your class notes or textbooks from previous courses on image processing.
  • Go through online tutorials or videos that cover the basics of image processing.
  • Complete practice exercises or quizzes to test your understanding of the concepts.
Read 'Computer Vision: Algorithms and Applications'
Supplement your learning by reading a comprehensive book on computer vision, covering a wide range of topics including feature detection and image processing.
View Computer Vision on Amazon
Show steps
  • Obtain a copy of the book 'Computer Vision: Algorithms and Applications'.
  • Read the chapters relevant to feature detection and image processing.
  • Take notes and highlight important concepts.
Follow Tutorials on Edge and Corner Detection
Enhance your understanding of edge and corner detection techniques by following guided tutorials that provide step-by-step instructions and examples.
Browse courses on Feature Detection
Show steps
  • Find online tutorials or courses that cover edge and corner detection algorithms.
  • Follow the instructions and implement the algorithms in a programming language of your choice.
  • Test your implementation on different images and analyze the results.
Five other activities
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Solve SIFT Detector Practice Problems
Strengthen your grasp of the SIFT detector by solving practice problems and implementing it in code.
Show steps
  • Find online practice problems or coding challenges related to the SIFT detector.
  • Implement the SIFT detector algorithm in a programming language of your choice.
  • Test your implementation on different images and evaluate its performance.
Write a Blog Post on Advanced Feature Detection Techniques
Enhance your understanding and communication skills by writing a blog post that explores advanced feature detection techniques and their applications.
Show steps
  • Research advanced feature detection techniques and gather relevant information.
  • Organize your content and outline the key points of your blog post.
  • Write the blog post, explaining the techniques clearly and providing examples.
Build a Simple Image Stitching Application
Apply your knowledge of feature detection and image stitching by building a functional image stitching application.
Browse courses on Image Stitching
Show steps
  • Design the architecture of your image stitching application.
  • Implement the core functionality for detecting features and stitching images.
  • Test your application on a variety of image sets and evaluate its performance.
Contribute to an Open-Source Image Processing Library
Gain practical experience and contribute to the community by working on an open-source image processing library to enhance your understanding of image processing algorithms.
Show steps
  • Identify an open-source image processing library that aligns with your interests.
  • Explore the library's codebase and documentation.
  • Identify an area where you can contribute, such as improving an existing algorithm or adding a new feature.
  • Make your contributions and submit a pull request.
Develop a Face Detection Algorithm
Challenge yourself by developing a face detection algorithm from scratch, applying your understanding of feature detection and classification techniques.
Browse courses on Face Detection
Show steps
  • Research different face detection algorithms and select an approach.
  • Implement the algorithm in a programming language of your choice.
  • Train the algorithm on a dataset of face images.
  • Evaluate the performance of your algorithm on a test set and make improvements as needed.

Career center

Learners who complete Features and Boundaries will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineers design, develop, and implement computer vision systems and applications. They work with computer vision algorithms and machine learning techniques to build systems that can interpret and understand images and videos. This course can be helpful for aspiring Computer Vision Engineers, as it provides a strong foundation in feature and boundary detection, which are critical for many computer vision applications.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models and algorithms. They work with large datasets and use machine learning techniques to build systems that can learn from data and make predictions. This course can be helpful for aspiring Machine Learning Engineers, as it provides a strong foundation in feature and boundary detection, which are important for many machine learning tasks.
Data Scientist
Data Scientists use data analysis techniques to extract insights from data. They work with large datasets and use statistical and machine learning techniques to identify patterns and trends in data. This course can be helpful for aspiring Data Scientists, as it provides a strong foundation in feature and boundary detection, which are important for many data analysis tasks.
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with programming languages and software development tools to build and test software systems. This course can be helpful for aspiring Software Engineers, as it provides a strong foundation in feature and boundary detection, which are important for many software development tasks.
Robotics Engineer
Robotics Engineers design, develop, and maintain robots and robotic systems. They work with mechanical, electrical, and computer engineering principles to build and test robots. This course can be helpful for aspiring Robotics Engineers, as it provides a strong foundation in feature and boundary detection, which are important for many robotics applications.
Computer Graphics Engineer
Computer Graphics Engineers design, develop, and maintain computer graphics systems and applications. They work with computer graphics algorithms and techniques to create realistic and interactive images and videos. This course can be helpful for aspiring Computer Graphics Engineers, as it provides a strong foundation in feature and boundary detection, which are important for many computer graphics applications.
Image Processing Engineer
Image Processing Engineers design, develop, and maintain image processing systems and applications. They work with image processing algorithms and techniques to enhance, analyze, and interpret images. This course can be helpful for aspiring Image Processing Engineers, as it provides a strong foundation in feature and boundary detection, which are important for many image processing applications.
Medical Imaging Analyst
Medical Imaging Analysts use medical imaging techniques to diagnose and treat diseases. They work with medical imaging equipment and software to create and analyze images of the body. This course can be helpful for aspiring Medical Imaging Analysts, as it provides a strong foundation in feature and boundary detection, which are important for many medical imaging applications.
Forensic Scientist
Forensic Scientists use scientific methods to investigate crimes and solve cases. They work with evidence and use forensic techniques to identify and analyze evidence. This course can be helpful for aspiring Forensic Scientists, as it provides a strong foundation in feature and boundary detection, which are important for many forensic applications.
Geologist
Geologists study the Earth's physical structure and history. They work with rocks, minerals, and fossils to understand the Earth's formation and evolution. This course can be helpful for aspiring Geologists, as it provides a strong foundation in feature and boundary detection, which are important for many geological applications.
Archaeologist
Archaeologists study human history and culture through the excavation and analysis of artifacts. They work with archaeological sites and artifacts to understand human behavior and the development of civilizations. This course can be helpful for aspiring Archaeologists, as it provides a strong foundation in feature and boundary detection, which are important for many archaeological applications.
Architect
Architects design and oversee the construction of buildings and other structures. They work with clients and contractors to create functional and aesthetically pleasing spaces. This course can be helpful for aspiring Architects, as it provides a strong foundation in feature and boundary detection, which are important for many architectural applications.
Interior designer
Interior Designers plan and design the interior spaces of buildings. They work with clients and contractors to create functional and aesthetically pleasing spaces. This course can be helpful for aspiring Interior Designers, as it provides a strong foundation in feature and boundary detection, which are important for many interior design applications.
Landscape Architect
Landscape Architects design and create outdoor spaces. They work with clients and contractors to create functional and aesthetically pleasing landscapes. This course can be helpful for aspiring Landscape Architects, as it provides a strong foundation in feature and boundary detection, which are important for many landscape architecture applications.
Urban Planner
Urban Planners plan and design cities and towns. They work with local governments and citizens to create livable and sustainable communities. This course may be helpful for aspiring Urban Planners, as it provides a strong foundation in feature and boundary detection, which are important for many urban planning applications.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Features and Boundaries.
Provides a comprehensive overview of computer vision algorithms and applications, including feature detection and boundary detection. It valuable resource for students and researchers in computer vision.
Provides a comprehensive overview of digital image processing, including edge detection and boundary detection. It valuable resource for students and researchers in computer vision.
Provides a modern approach to computer vision, including feature detection and boundary detection. It valuable resource for students and researchers in computer vision.
Provides a comprehensive overview of face detection and recognition. It valuable resource for students and researchers in computer vision.
Provides a comprehensive overview of pattern recognition and machine learning, including feature detection and boundary detection. It valuable resource for students and researchers in computer vision.
Provides a comprehensive overview of multiple view geometry in computer vision. It valuable resource for students and researchers in computer vision.
Provides a comprehensive overview of computer vision for visual effects. It valuable resource for students and researchers in computer vision.
Provides a comprehensive overview of computer vision and image processing. It valuable resource for students and researchers in computer vision.

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