The purpose of this study is to present a depth information-based solution for automatic camera control, depending on the presenter’s moving positions. Talks, presentations and lectures are often captured on video to give a broad audience the possibility to (re-)access the content. As presenters are often moving around during a talk, it is necessary to steer recording cameras.
We use depth information from Kinect to implement a prototypical application to automatically steer multiple cameras for recording a talk.
We present our experiences with the system during actual lectures at a university. We found out that Kinect is applicable for tracking a presenter during a talk robustly. Nevertheless, our prototypical solution reveals potential for improvements, which we discuss in our future work section.
Tracking a presenter is based on a skeleton model extracted from depth information instead of using two-dimensional (2D) motion- or brightness-based image processing techniques. The solution uses a scalable networking architecture based on publish/subscribe messaging for controlling multiple video cameras.
Winkler, M., Michael Höver, K. and Mühlhäuser, M. (2014), "A depth camera based approach for automatic control of video cameras in lecture halls", Interactive Technology and Smart Education, Vol. 11 No. 3, pp. 169-183. https://doi.org/10.1108/ITSE-06-2014-0012Download as .RIS
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