Commands generation by face movements applied to the guidance of a wheelchair for handicapped people

Describes a vision-based commands generation system, by face movements, applied to the guidance of an electric wheelchair for handicapped people with severe disabilities. Using a 2D color face tracker and a fuzzy detector the system computes face movements of the user and, depending on them, some commands are generated to drive the wheelchair. The system is non-intrusive and it allows visibility and freedom of head movements. It is able to learn the face movements of the user in an automatic initial setup, working even for people of different races. It is adaptive and, therefore, robust to light and background changes in inside environments. We report on some experimental results of this kind of guidance and some conclusions about its performance.