Reference Work Entry

Machine Vision Handbook

pp 89-115

Human and Animal Vision

  • Jonathan T. ErichsenAffiliated withCardiff School of Optometry and Vision Sciences, Cardiff University Email author 
  • , J. Margaret WoodhouseAffiliated withCardiff School of Optometry and Vision Sciences, Cardiff University

Abstract

Since this is a book about artificial vision, it may seem strange that we include an essay on vision in the natural world. The reason is simple: we need to convince the reader that there is no single model for vision that is ideal for all circumstances. Our own visual system, sophisticated though it is, would not suit a housefly, eagle, owl, chameleon, or even a horse. Each of these animals has managed to thrive within a specific type of environment, for far longer than human beings have walked on two legs. Even though it is very limited in its visual capability compared to human beings, a frog has a vision system that has served it well for many millions of years. In many instances, an industrial Machine Vision system is like a frog: both can do certain well-defined tasks, without attempting to achieve the subtlety of discrimination and the high level of intelligent scene analysis that a human being can accomplish. In nature, there are four scenes that nearly every organism has to recognise: food, threat, mate, and shelter. This is not so very different from an inspection system that is merely intended to distinguish between ‘good’ and ‘faulty’ products. Animals do, however, have to cope with highly variable environments and cannot change the viewing conditions as a vision engineer can do to make his/her creation cheaper, faster, or more reliable. So, our task is usually simpler than designing a machine as complex as a frog. We must never make the mistake of thinking that only we see the world as it really is. We are only sensitive to a narrow range of optical wavelengths. We cannot sense polarisation, whereas bees and appropriately designed machines can. We cannot sense very low light levels that some animals have to use. Why should we want to replicate a system like ours that is confused by numerous visual illusions? The natural world has produced many different models for vision. For example, there are over 40 different types of eye. The compound eye of the insects and our own eye are obviously very different. Even the eye of a relatively close relation, the cat, is significantly different from our own, having a vertical pupil in bright light. Some animal eyes move the lens to focus on objects that are moving along the line of sight, rather than alter the shape of the lens, as our own eyes do. There is nothing particularly special about our colour vision either. Mantis shrimps, for example, have 12 different colour pigments in their eyes. Spiders are not content with just two eyes as we are; they have eight! This variety does more than present us with a collection of interesting curiosities; it provides inspiration! Vision engineers can benefit from learning about non-human vision systems. Perhaps the most important point of all is that vision engineers should have the confidence to be different; we should not be constrained always to try and emulate human vision. Nature isn’t! Although it is immensely powerful, human vision is sometimes ineffective, and in other cases grossly over-sophisticated, for the humble tasks required of industrial vision systems. It is always vain to do with more what can be done with less. So, if frog vision works, use it!

Vision is pervasive in the animal kingdom and is a sensory capability that is variously relied upon to find reproductive mates, suitable food, and/or shelter while avoiding predators or other dangers. The receptor organs (e.g., eyes) and associated visual system not only provide the basis for visual perception of the surrounding environment but also drive and guide the visuomotor responses (e.g., locomotion, eye movements, reaching to grasp, etc.) in reaction to changes or objects of interest in the world. Although animal vision has intrinsic limits that vary from species to species as well as different properties (e.g., colour vision) that may arise for specific purposes in the course of evolution, its main characteristic is that it represents a generalised adaptation that can deal with a diverse range of problems and challenges. In contrast, machine vision is narrowly designed for a particular purpose or function and its related systems are normally highly constrained. This chapter offers a broad summary of human and animal vision, with an emphasis on vertebrates, paying particular attention not only to its basic design properties and limitations but also the sheer diversity of biological solutions to the problem of perceiving the world and responding appropriately. The hope is that such an examination of vision from a variety of perspectives will inform and inspire the future design and engineering of machine vision.