000 Informatik, Informationswissenschaft, allgemeine Werke
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Live-Video-Broadcasting mit mehreren Kameras erfordert eine Vielzahl von Fachkenntnissen. Robotersysteme ermöglichen zwar die Automatisierung von gängigen und wiederholten Tracking-Aufnahmen, diese erlauben jedoch keine kurzfristigen Anpassungen aufgrund von unvorhersehbaren Ereignissen. In diesem Beitrag wird ein modulares, automatisiertes Kamerasteuerungs- und Bildschnitt-System eingeführt, das auf grundlegenden kinematografischen Regeln basiert. Die Positionen der Akteure werden durch ein markerloses Tracking-System bereitgestellt. Darüber hinaus werden Tonpegel der Lavaliermikrofone der Akteure zur Analyse der aktuellen Szene verwendet. Ein Expertensystem ermittelt geeignete Kamerawinkel und entscheidet, wann von einer Kamera auf eine andere umgeschaltet werden soll. Eine Testproduktion wurde durchgeführt, um den entwickelten Prototyp in einem Live-Broadcast-Szenario zu beobachten und diente als Videodemonstration für eine Evaluierung.
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.
Shadows in computer graphics are an important rendering aspect for spatial objects. For realtime computer applications such as games, it is essential to represent shadows as accurate as possible. Also, various tv stations work with virtual studio systems instead of real studio sets. Especially for those systems, a realistic impression of the rendered and mixed scene is important. One challenge, hence, is the creation of a natural shadow impression. This paper presents the results of an empirical study to compare the performance and quality of different shadow mapping methods. For this test, a prototype studio renderer was developed. A percentage closer filter (pcf) with a number of specific resolutions is used to minimize the aliasing issue. More advanced algorithms which generate smooth shadows like the percentage closer soft shadow (pcss) method as well as the variance shadow maps (vsm) method are analysed. Different open source apis are used to develop the virtual studio renderer, giving the benefit of permanent enhancement. The Ogre 3D graphic engine is used to implement the rendering system, benefiting from various functions and plugins. The transmission of the tracking data is accomplished with the vrpn server/client and the Intersense api. The different shadow algorithms are compared in a virtual studio environment which also casts real shadows and thus gives a chance for a direct comparison throughout the empirical user study. The performance is measured in frames per secon