Computer Vision for Assistive Healthcare (Computer Vision and Pattern Recognition)

Computer Vision for Assistive Healthcare describes how advanced computer vision techniques provide tools to support common human needs, such as mental functioning, personal mobility, sensory functions, daily living activities, image processing, pattern recognition, machine learning and how language processing and computer graphics cooperate with robotics to provide such tools. Users will learn about the emerging computer vision techniques for supporting mental functioning, algorithms for analyzing human behavior, and how smart interfaces and virtual reality tools lead to the development of advanced rehabilitation systems able to perform human action and activity recognition.

In addition, the book covers the technology behind intelligent wheelchairs, how computer vision technologies have the potential to assist blind people, and about the computer vision-based solutions recently employed for safety and health monitoring.

• Gives the state-of-the-art computer vision techniques and tools for assistive healthcare
• Includes a broad range of topic areas, ranging from image processing, pattern recognition, machine learning to robotics, natural language processing and computer graphics
• Presents a wide range of application areas, ranging from mobility, sensory substitution, and safety and security, to mental and physical rehabilitation and training
• Written by leading researchers in this growing field of research
• Describes the outstanding research challenges that still need to be tackled, giving researchers good indicators of research opportunities

Marco Leo received an Honours Degree in Computer Science Engineering from the University of Salento (Italy) in 2001. Currently he is a Researcher at the National Research Council of Italy. His main research interests are in the fields of image and signal processing and analysis, computer vision, pattern recognition, neural networks, graphical models, linear and non-linear transformation (Fourier, Wavelet, ICA, kernels functions). He participated in a number of national and international research projects focusing on assistive technologies, automatic video surveillance of indoor and outdoor environments, human attention monitoring, real-time event detection in sport contexts and non-destructive inspection of aircraft components. He is author of more than 100 papers in national and international journals, and conference proceedings. He is also a co-author of three international patents on visual systems for event detection in sport contexts.

Giovanni Maria Farinella obtained a degree in Computer Science (egregia cum laude) from the University of Catania, Italy, in 2004. He joined as Internal Member of the IPLAB Research Group at University of Catania in 2005. He also became an Associate Member of the Computer Vision and Robotics Research Group at University of Cambridge in 2006. He was awarded a Doctor of Philosophy (Computer Vision) from the University of Catania in 2008. He is currently a Researcher at the Department of Mathematics and Computer Science, University of Catania, Italy. His research interests lie in the fields of Computer Vision, Image Analysis, Computer Graphics, Pattern Recognition and Machine Learning. Giovanni Maria Farinella founded (in 2006) and currently directs the International Computer Vision Summer School.