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Shree Nayar

The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception.

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The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception.

We first describe the problem of tracking objects in complex scenes. We look at two key challenges in this context. The first is the separation of an image into object and background using a technique called change detection. The second is the tracking of one or more objects in a video. Next, we examine the problem of segmenting an image into meaningful regions. In particular, we take a bottom-up approach where pixels with similar attributes are grouped together to obtain a region.

Finally, we tackle the problem of object recognition. We describe two approaches to the problem. The first directly recognize an object and its pose using the appearance of the object. This method is based on the concept of dimension reduction, which is achieved using principal component analysis. The second approach is to use a neural network to solve the recognition problem as one of learning a mapping from the input (image) to the output (object class, object identity, activity, etc.). We describe how a neural network is constructed and how it is trained using the backpropagation algorithm.

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What's inside

Syllabus

Getting Started: Visual Perception
Object Tracking
Image Segmentation
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Appearance Matching
Neural Networks

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides foundational knowledge and understanding of the field of computer vision
Develops practical skills for object tracking, segmentation, feature matching, and recognition
Taught by Shree Nayar, a leading expert in computer vision
Examines current trends and applications of computer vision, making the course relevant to industry
Suitable for learners with some background in computer science, making it accessible to a wider audience
May require additional resources and materials not readily available, such as software and datasets

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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 Visual Perception with these activities:
Review linear algebra
Recall and practice linear algebra skills to improve understanding of object tracking and recognition.
Browse courses on Linear Algebra
Show steps
  • Review lecture notes and textbooks on linear algebra concepts.
  • Solve practice problems and exercises to reinforce understanding.
  • Utilize online resources and tutorials for additional support.
Explore OpenCV tutorials
Gain familiarity with OpenCV, a popular computer vision library, to enhance understanding of image segmentation and object recognition.
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Show steps
  • Access the OpenCV documentation and tutorials.
  • Follow step-by-step tutorials on image processing and object detection.
  • Experiment with OpenCV functions and explore code examples.
Image annotation practice
Develop proficiency in image annotation to enhance object recognition skills and contribute to computer vision datasets.
Show steps
  • Register on platforms like Amazon Mechanical Turk or Labelbox.
  • Follow guidelines and instructions for image annotation.
  • Annotate images accurately and consistently.
Two other activities
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Show all five activities
Develop a computer vision project
Apply computer vision techniques to solve a real-world problem, demonstrating understanding and practical skills.
Browse courses on Object Tracking
Show steps
  • Identify a problem or application for computer vision.
  • Research and design a solution using appropriate computer vision techniques.
  • Implement the project using programming languages and libraries.
  • Evaluate the performance and accuracy of the project.
Participate in computer vision forums
Engage with others in the field, share knowledge, and assist fellow learners to deepen understanding and expand perspectives.
Browse courses on Online Communities
Show steps
  • Join online forums or communities focused on computer vision.
  • Participate in discussions, answer questions, and share resources.
  • Connect with other learners and professionals.

Career center

Learners who complete Visual Perception will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
A Computer Vision Engineer designs, develops, and maintains computer vision systems, which are used in various applications such as object recognition, image segmentation, and tracking. This course would provide a solid foundation in the principles and techniques of visual perception, which is essential for success in this role. The course covers topics such as object tracking, image segmentation, appearance matching, and neural networks, all of which are relevant to the work of a Computer Vision Engineer.
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and maintains machine learning models, which are used in a variety of applications such as natural language processing, image recognition, and predictive analytics. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of many machine learning applications. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Machine Learning Engineer.
Data Scientist
A Data Scientist uses data to build models that can be used to make predictions or decisions. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of many data science applications. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Data Scientist.
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of many software applications. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Software Engineer.
Robotics Engineer
A Robotics Engineer designs, develops, and maintains robots. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of many robotics applications. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Robotics Engineer.
Computer Graphics Artist
A Computer Graphics Artist creates visual content for various applications such as movies, video games, and advertising. This course would provide a solid foundation in the principles and techniques of visual perception, which is essential for success in this role. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Computer Graphics Artist.
User Experience Designer
A User Experience Designer designs and evaluates user interfaces for various applications such as websites, mobile apps, and software programs. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of user experience design. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a User Experience Designer.
Product Manager
A Product Manager is responsible for the development and management of a product. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of product development. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Product Manager.
Marketing Manager
A Marketing Manager is responsible for the development and execution of marketing campaigns. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of marketing. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Marketing Manager.
Sales Manager
A Sales Manager is responsible for the development and execution of sales strategies. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of sales. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Sales Manager.
Customer Success Manager
A Customer Success Manager is responsible for the development and execution of customer success strategies. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of customer success. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Customer Success Manager.
Business Analyst
A Business Analyst is responsible for the analysis and improvement of business processes. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of business analysis. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Business Analyst.
Consultant
A Consultant is responsible for providing advice and guidance to clients on a variety of business issues. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of consulting. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Consultant.
Project Manager
A Project Manager is responsible for the planning and execution of projects. This course would provide a solid foundation in the principles and techniques of visual perception, which is an important aspect of project management. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Project Manager.
Teacher
A Teacher is responsible for the education and development of students. This course may be useful for teachers who want to learn more about the principles and techniques of visual perception. The course covers topics such as object tracking, image segmentation, and neural networks, all of which are relevant to the work of a Teacher.

Reading list

We've selected nine 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 Visual Perception.
Provides a computational approach to visual perception. It would be a valuable resource for students taking this course who want to learn more about the theoretical foundations of visual perception.
Provides an overview of deep learning. It would be a valuable resource for students taking this course who want to learn more about the foundations of deep learning.
Provides a comprehensive overview of brain theory and neural networks. It would be a valuable resource for students taking this course who want to learn more about the neural basis of visual perception.
Provides a comprehensive overview of computer vision algorithms and their applications. It would be a useful reference for students taking this course, as it covers many of the same topics in more depth.
Provides an overview of pattern recognition and machine learning. It would be a valuable resource for students taking this course who want to learn more about the machine learning techniques used in computer vision.
Provides an overview of deep learning for computer vision. It would be a valuable resource for students taking this course who want to learn more about the deep learning techniques used in computer vision.
Provides a practical approach to digital image processing. It would be a valuable resource for students taking this course who want to learn more about the image processing techniques used in computer vision.
Provides an overview of OpenCV 4 computer vision with Python. It would be a valuable resource for students taking this course who want to learn more about the OpenCV library and how to use it for computer vision tasks.
Provides an overview of computer graphics. It would be a valuable resource for students taking this course who want to learn more about the computer graphics techniques used in computer vision.

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