TY - CHAP A1 - Ballester Ripoll, Marina A1 - Herder, Jens A1 - Ladwig, Philipp A1 - Vermeegen, Kai ED - Pfeiffer, Thies ED - Fröhlich, Julia ED - Kruse, Rolf T1 - Comparison of two Gesture Recognition Sensors for Virtual TV Studios T2 - GI-VRAR, Workshop Proceedings / Tagungsband: Virtuelle und Erweiterte Realität – 13. Workshop der GI-Fachgruppe VR/AR, N2 - In order to improve the interactivity between users and computers, recent technologies focus on incorporating gesture recognition into interactive systems. The aim of this article is to evaluate the effectiveness of using a Myo control armband and the Kinect 2 for recognition of gestures in order to interact with virtual objects in a weather report scenario. The Myo armband has an inertial measurement unit and is able to read electrical activity produced by skeletal muscles, which can be recognized as gestures, which are trained by machine learning. A Kinect sensor was used to build up a dataset which contains motion recordings of 8 different gestures and was also build up by a gesture training machine learning algorithm. Both input methods, the Kinect 2 and the Myo armband, were evaluated with the same interaction patterns in a user study, which allows a direct comparison and reveals benefits and limits of each technique. KW - Gesture recognition KW - Interaction KW - Kinect KW - Myo KW - Virtual (TV) Studio KW - Lehre Y1 - 2016 UR - http://vsvr.medien.hs-duesseldorf.de/publications/gi-vrar2016-gesture-abstract.html SN - 978-3-8440-4718-9 PB - Shaker Verlag CY - Herzogenrath ER - TY - CHAP A1 - Daemen, Jeff A1 - Herder, Jens A1 - Koch, Cornelius A1 - Ladwig, Philipp A1 - Wiche, Roman A1 - Wilgen, Kai T1 - Semi-Automatic Camera and Switcher Control for Live Broadcast T2 - TVX '16 Proceedings of the ACM International Conference on Interactive Experiences for TV and Online Video, Chicago, Illinois, USA — June 22 - 24, 2016 N2 - Live video broadcasting requires a multitude of professional expertise to enable multi-camera productions. Robotic systems allow the automation of common and repeated tracking shots. However, predefined camera shots do not allow quick adjustments when required due to unpredictable events. We introduce a modular automated robotic camera control and video switch system, based on fundamental cinematographic rules. The actors' positions are provided by a markerless tracking system. In addition, sound levels of actors' lavalier microphones are used to analyse the current scene. An expert system determines appropriate camera angles and decides when to switch from one camera to another. A test production was conducted to observe the developed prototype in a live broadcast scenario and served as a video-demonstration for an evaluation. KW - automated robotic camera system KW - actor tracking KW - switcher control KW - scene analysis KW - film rules KW - automated shot control KW - Virtual (TV) Studio Y1 - 2016 UR - http://vsvr.medien.hs-duesseldorf.de/publications/tvx2016-rob-abstract.html SN - 978-1-4503-4067-0 U6 - https://doi.org/10.1145/2932206.2933559 SP - 129 EP - 134 PB - ACM CY - New York ER -