A depth camera based approach for automatic control of video cameras in lecture halls. Issue 3 (19th August 2014) - Winkler, Michael; Höver, Kai Michael; Mühlhäuser, Max
Abstract : Purpose: 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 present a depth information based solution for automatic camera control depending on the presenter's moving positions. Design/methodology/approach: We use depth information from Kinect to implement a prototypical application to automatically steer multiple cameras for recording a talk. Findings: 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. Originality/value: Tracking a presenter is based on a skeleton model extracted from depth information instead of using 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.