Abstract
This paper addresses the problem of head pose estimation (HPE) for digital signage systems. Because the HPE which estimates the roll, pitch and yaw angles of human heads can extract not only the existence of human faces but also additional information, it is expected that the HPE can play an important role in digital signage systems. However, for the quality of the additional information, the HPE needs to be accurately conducted. This paper presents various performance evaluation results of the HPE methods which are non-deep learning-based and deep learning-based methods. The HPE methods in this work are implemented based on the existing open-sources. Their accuracy was evaluated with the public datasets by comparing the estimated angles and the true angles in the public datasets.
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.
