Learning and recognition for assistive computer vision

Scope Assistive Computer Vision refers to systems that support people with physical and mental problems to better perform daily tasks enhancing their quality of life. The advances in learning and recognizing patterns are allowing a point of view in the definition and development of more efficient and effective assistive frameworks. In the light of this, it is important to collect the most recent advancements in learning and recognition algorithms to be exploited in different applications to be employed to assist the modern society. The aim of the special issue is to gather papers in which machine learning and pattern recognition are the key core in the design of advanced assistive computer vision systems to help human in tasks such as: • Rehabilitation • Training • Mobility • Assessment and diagnosis of physical and cognitive diseases • Improving quality of Life • Remote Healthcare • Safe and security • Remote Surgery • Ambient Assisted Living • Augmented Perception, Attention and Memory