Making a Machine That Sees Like Us [Hardcover]

Making a Machine That Sees Like Usexplains why and how our visual perceptions can provide us with an accurate representation of the external world. Along the way, it tells the story of a machine (a computational model) built by the authors that solves the computationally difficult problem of seeing the way humans do. This accomplishment required a radical paradigm shift - one that challenged preconceptions about visual perception and tested the limits of human behavior-modeling for practical application.

The text balances scientific sophistication and compelling storytelling, making it accessible to both technical and general readers. Online demonstrations and references to the authors' previously published papers detail how the machine was developed and what drove the ideas needed to make it work. The authors contextualize their new theory of shape perception by highlighting criticisms and opposing theories, offering readers a fascinating account not only of their revolutionary results, but of the scientific process that guided the way.

Making a Machine That Sees Like Us

1. How the Stage Was Set When We Began

1.1 Introduction
1.2 What is this book about?
1.3 Analytical and Operational definitions of shape
1.4 Shape constancy as a phenomenon (something you can observe)
1.5 Complexity makes shape unique
1.6 How would the world look if we are wrong?
1.7 What had happened in the real world while we were away
1.8 Perception viewed as an Inverse Problem
1.9 How Bayesian inference can be used for modeling perception
1.10 What it means to have a model of vision, and why we need to have one
1.11 End of the beginning.

2. How This All Got Started

2.1 Controversy about shape constancy: 1980 - 1995
2.2 Events surrounding the 29th European Conference on Visual Perception (ECVP), St. Petersburg, Russia, August 20 - 25, 2006 where we first announced our paradigm shift
2.3 The role of clH