Robotic Vision: Technologies for Machine Learning and Vision Applications
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Robotic Vision: Technologies for Machine Learning and Vision Applications

Jose Garcia-Rodriguez (University of Alicante, Spain) and Miguel A. Cazorla Quevedo (University of Alicante, Spain)
Indexed In: SCOPUS View 2 More Indices
Release Date: December, 2012|Copyright: © 2013 |Pages: 535
DOI: 10.4018/978-1-4666-2672-0
ISBN13: 9781466626720|ISBN10: 1466626720|EISBN13: 9781466627031
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Description & Coverage
Description:

Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed.

Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Computer Vision
  • Face Recognition
  • Human Robot Interaction
  • Multi-Component Robotic Systems
  • Task Learning for Robots
  • Visual Control
  • Visual Detection
  • Visual Learning in Robots
Reviews and Testimonials

For researchers and practitioners in computer vision and robotics, García-Rodríguez and Cazorla Quevedo (computer technology and artificial intelligence, U. of Alicante, Spain) bring together computer science, engineering, robotics, and technology researchers from Europe, South America, and the US for 22 chapters on computer vision and its applications. They discuss computer vision basics and applications, including face recognition, uniform sampling of rotations for discrete and continuous learning of 2D shape models, basic segmentation methods of video sequences and their combinations, video security systems, visual detection in a linked multi-component robotic systems, building a multiple object tracking system with occlusion handling in surveillance videos, and self-organizing neural networks; 3D data processing applied robotics, with discussion of registration methods for mobile robots, evaluating disparity estimation algorithms, real-time structure estimation in dynamic scenes using a single camera, and intelligent stereo vision in autonomous robot traversability estimation; social robotics systems, such as for imitating gestures, learning to interact socially with humans, assisted living, and human-robot interaction; vision control; and visual attention.

– Annotation ©2013 Book News Inc. Portland, OR
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Editor/Author Biographies
José García Rodríguez received his BSc, MSc and Phd in Computer Science from the University of Alicante (Spain) in 1994, 1996 and 2009 respectively. He is currently a Professor in the Department of Computer Technology at the University of Alicante. His research interest are focused on computer vision, neural networks, man-machine interaction, ambient intelligence, robotics and algorithms parallelization and acceleration.
Miguel Cazorla received a BS degree in Computer Science from the University of Alicante (Spain) in 1995 and a PhD in Computer Science from the same University in 2000. He is currently Associate Professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante. He has done several postdocs stays: ACFR at University of Sydney with Eduardo Nebot, IPAB at University of Edinburgh with Robert Fisher, CMU with Sebastian Thrun and SKERI with Alan Yuille. He has published several papers on robotics and computer vision. His research interest are focused on computer vision and mobile robotics (mainly using vision to implement robotics tasks).
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