Abstract
To eliminate barriers to communication between social robots and disabled people in listening and/or speaking, this work proposes a gesture recognition method that is based on the region of interest (ROI) and a convolutional neural network (CNN) for social robots. This method can track and recognize gestures in real time in a complex background. ROI and OpenCV are first used to obtain the dynamic gesture, which is then treated as the input of a CNN model to output a gesture feature model. Furthermore, a gesture-controlled social robot is implemented by the obtained feature model. Finally, the performance of the system is verified, and experimental results show that the proposed technology can track and recognize user gestures in real time.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
