Computer Vision for Learning to Interact Socially with Humans

Computer Vision for Learning to Interact Socially with Humans

Renato Ramos da Silva (Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil) and Roseli Aparecida Francelin Romero (Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil)
Copyright: © 2013 |Pages: 26
DOI: 10.4018/978-1-4666-3994-2.ch059
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Abstract

Computer vision is essential to develop a social robotic system capable to interact with humans. It is responsible to extract and represent the information around the robot. Furthermore, a learning mechanism, to select correctly an action to be executed in the environment, pro-active mechanism, to engage in an interaction, and voice mechanism, are indispensable to develop a social robot. All these mechanisms together provide a robot emulate some human behavior, like shared attention. Then, this chapter presents a robotic architecture that is composed with such mechanisms to make possible interactions between a robotic head with a caregiver, through of the shared attention learning with identification of some objects.
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Background

Computer vision researches aim to extract information from images using many ways, such as video sequences, views from multiple cameras, or multi-dimensional data. It helps to solve some task, or “understand” the scene in either a broad or limited sense. Applications range from industrial machine vision systems which operate in a production line, medicine helping in disease medical diagnostic to artificial intelligence, helping to the computers or robots to comprehend better the world around them.

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