V. García1 N. Sánchez1, J.A. Rodrigo1, J.M. Menéndez2, and J. Lalueza1
1Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
2Grupo de Aplicación de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Madrid, Spain
6.1 Introduction: Machine Vision and the Proliferation of Smart Internet of Things Driven Environments
One of the most ambitious goals of machine vision research is that devices used for processing data, regardless of their nature, will achieve similar capabilities to the human's visual and cognitive system, as anticipated in the introduction of this book. This will enable systems, for example, to recognize different objects occurring in an image [1] and will offer them increased autonomy, thereby reducing the level of active human involvement in human–computer shared tasks.
From both a visual and cognitive point of view, any system oriented to mimic human abilities should be able to perform three key vision‐related tasks: perception, interpretation, and learning, as depicted in Figure 6.1.
Figure 6.1 Perception, interpretation, and learning in the IoT ecosystem.
Perception is the process of attaining awareness or understanding of the environment by processing input sensory information, which is often incomplete and rapidly varying. Thus, machine vision systems rely on data gathered by different kinds of sensors (predominantly ...
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