The best books on computer vision from a 40-year veteran professor who wrote one

Why am I passionate about this?

It’s been fantastic to work in computer vision, especially when it is used to build biometric systems. I and my 80 odd PhD students have pioneered systems that recognise people by the way they walk, by their ears, and many other new things too. To build the systems, we needed computer vision techniques and architectures, both of which work with complex real-world imagery. That’s what computer vision gives you: a capability to ‘see’ using a computer. I think we can still go a lot further: to give blind people sight, to enable better invasive surgery, to autonomise more of our industrial society, and to give us capabilities we never knew we’d have.


I wrote...

Feature Extraction and Image Processing for Computer Vision

By Mark S. Nixon,

Book cover of Feature Extraction and Image Processing for Computer Vision

What is my book about?

Computer Vision now helps society in many ways: we use face recognition on our phones and we can identify plants too (though we sometimes get fined when our number/ license plate goes past a camera too quickly). The advance has been due to faster computers, cheaper memory, better sensors, and better techniques. Back in 1997 I and Alberto found that no book covered feature extraction in-depth, so we rectified that. Our book is pretty much the only one describing computer vision via techniques for finding and describing shapes and structure. Many of these now find use in the systems applied in medicine and in industry – and in current deep learning-based systems. I’ll next be listing some of the great books that have moved this fascinating field forwards.

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The books I picked & why

Book cover of Vision: A Computational Investigation into the Human Representation and Processing of Visual Information

Mark S. Nixon Why did I love this book?

David Marr shaped the field of computer vision in its early days. His seminal book laid the structure for interpreting images and one which is still largely followed. He popularised notions of the primal sketch and his work on edge detection led to one of the most sophisticated approaches. His work and influence continue to endure despite his early death: we missed and miss him a lot.

By David Marr,

Why should I read it?

1 author picked Vision as one of their favorite books, and they share why you should read it.

What is this book about?

Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions.

David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This…


Book cover of Multiple View Geometry in Computer Vision

Mark S. Nixon Why did I love this book?

Adding perspective puzzled artists in the fourteenth century; analysing perspective is integral to applied computer vision. You might have seen Hawkeye in action: the principles by which it works are explained superbly within this book. It was the first of its kind to set this analysis in a lucid and compelling format. Richard and Andrew’s text will be on researchers’ bookshelves for many years for its bedrock description of how we analyse three-dimensional scenes.

By Richard Hartley, Andrew Zisserman,

Why should I read it?

1 author picked Multiple View Geometry in Computer Vision as one of their favorite books, and they share why you should read it.

What is this book about?

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has…


Book cover of Computer Vision: Models, Learning, and Inference

Mark S. Nixon Why did I love this book?

This fine book is about learning the relationships between what is seen in an image, and what is known about the world. It’s a counterpart to our book on feature extraction and it shows you what can be achieved with the features. It’s not for those who shy from maths, as is the case for all of the books here. So that you can build the techniques, Simon’s book also includes a wide variety of algorithms to help you on your way.

By Simon J.D. Prince,

Why should I read it?

1 author picked Computer Vision as one of their favorite books, and they share why you should read it.

What is this book about?

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build…


Book cover of Computer Vision: Algorithms and Applications

Mark S. Nixon Why did I love this book?

Richard’s authoritative leading textbook excellently describes the whole field of computer vision. It starts with the sensor, moves to image formation followed by feature extraction and grouping, and then by vision analysis. It’s pragmatic too, with excellent descriptions of applications. And there is a ton of support material. This is a mega textbook describing the whole field of computer vision.

By Richard Szeliski,

Why should I read it?

1 author picked Computer Vision as one of their favorite books, and they share why you should read it.

What is this book about?

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.

More than just a source of "recipes," this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are…


Book cover of Advanced Methods and Deep Learning in Computer Vision

Mark S. Nixon Why did I love this book?

The advances of deep learning have been awesome, and fast. It’s been hard for the textbooks to keep up, so it’s good to include one that describes the advances and state of art very well. It seems appropriate that it’s edited by two leading researchers who are Roy – who described computer vision systems implementations in a long series of excellent books – and Matt, whose work on face recognition revolutionised and transformed the progress of face recognition in the 1990s. This book gives you an image of where we are now in computer vision, and where we are going. 

By E.R. Davies (editor), Matthew Turk (editor),

Why should I read it?

1 author picked Advanced Methods and Deep Learning in Computer Vision as one of their favorite books, and they share why you should read it.

What is this book about?

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5-10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection.

This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as…


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Mindleap: A Fresh View of Education Empowered by Neuroscience and Systems Thinking

By Jim Brown,

Book cover of Mindleap: A Fresh View of Education Empowered by Neuroscience and Systems Thinking

Jim Brown Author Of Mindleap: A Fresh View of Education Empowered by Neuroscience and Systems Thinking

New book alert!

Why am I passionate about this?

I have spent my entire professional life quietly patrolling the frontiers of understanding human consciousness. I was an early adopter in the burgeoning field of biofeedback, then neurofeedback and neuroscience, plus theory and practices of humanistic and transpersonal psychology, plus steeping myself in systems theory as a context for all these other fields of focus. I hold a MS in psychology from San Francisco State University and a PhD from Saybrook Institute. I live in Mount Shasta CA with Molly, my life partner for over 60 years. We have two sons and two grandchildren.

Jim's book list on brain, mind, and consciousness

What is my book about?

In this thoroughly researched and exquisitely crafted treatise, Jim Brown synthesizes the newest understandings in neuroscience, developmental psychology, and dynamical systems theory for educators and others committed to nurturing human development.

He explains complex concepts in down-to-earth terms, suggesting how these understandings can transform education to engender optimal learning and intelligence. He explores the nature of consciousness, intelligence, and mind.

Brown then offers a model of optimal human learning through lifelong brain development within a supportive culture--drawing on the work of Piaget, Erickson, Maslow, Kohlberg, and Steiner--and how that work is being vastly expanded by neuroscience and dynamical systems thinking.

Mindleap: A Fresh View of Education Empowered by Neuroscience and Systems Thinking

By Jim Brown,

What is this book about?

In this thoroughly-researched and exquisitely crafted treatise, Jim Brown synthesizes the newest understandings in neuroscience, developmental psychology, and dynamical systems theory for educators and others committed to nurturing human development. He explains complex concepts in down-to-earth terms, suggesting how these understandings can transform education to truly engender optimal learning and intelligence. He explores the nature of consciousness, intelligence, and mind. Brown then offers a model of optimal human learning through life-long brain development within a supportive culture--drawing on the work of Piaget, Erickson, Maslow, Kohlberg, and Steiner--and how that work is being vastly expanded by neuroscience and dynamical systems thinking.


5 book lists we think you will like!

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