The visual detection and recognition of human actions by technical systems is a fundamental problem with many applications the human-computer interaction domain. Activities involving hand-object interactions and action sequences in goal-oriented tasks, such as manufacturing work, pose a particular challenge. We use deep learning to detect and recognize such actions in real-time, and we propose an assistance system that provides the user with feedback and guidance based on the recognized actions.
The visual detection and recognition of human actions by technical systems is a fundamental problem with many applications the human-computer interaction domain. Activities involving hand-object interactions and action sequences in goal-oriented tasks, such as manufacturing work, pose a particular challenge. We use deep learning to detect and recognize such actions in real-time, and we propose an assistance system that provides the user with feedback and guidance based on the recognized actions.