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

Who am I?

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.

The books I picked & why

Shepherd is reader supported. We may earn an affiliate commission when you buy through links on our website. This is how we fund this project for readers and authors (learn more).

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

By David Marr,

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

Why 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.


Multiple View Geometry in Computer Vision

By Richard Hartley, Andrew Zisserman,

Book cover of Multiple View Geometry in Computer Vision

Why 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.


Computer Vision: Models, Learning, and Inference

By Simon J. D. Prince,

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

Why 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.


Computer Vision: Algorithms and Applications

By Richard Szeliski,

Book cover of Computer Vision: Algorithms and Applications

Why 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.


Advanced Methods and Deep Learning in Computer Vision

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

Book cover of Advanced Methods and Deep Learning in Computer Vision

Why 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. 


5 book lists we think you will like!

Interested in computer vision, machine learning, and visual perception?

5,809 authors have recommended their favorite books and what they love about them. Browse their picks for the best books about computer vision, machine learning, and visual perception.

Computer Vision Explore 7 books about computer vision
Machine Learning Explore 31 books about machine learning
Visual Perception Explore 11 books about visual perception

And, 3 books we think you will enjoy!

We think you will like Advances in Financial Machine Learning, The Elements of Statistical Learning, and Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow if you like this list.