Computer Vision for Assistive Healthcare

1. Computer Vision to see
2. Computer Vision for Cognition
3. Computer Vision for physical rehabilitation and training
4. Computer Vision for CADsystems in surgery
5. Computer Vision for human-machine interaction
6. Computer Vision for Ambient Assisted Living
7. Egocentric (first person) vision
8. Augmented and alternative communication
9. Life logging
10. Vision for Social and Affective Robotics
11. Computer Vision for Safety and Security
Visual Question Answering

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

Researchers and graduate students in computer vision