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Die Informationsbroschüre „Elektromobilität in einer vernetzten Welt“ richtet sich an IT-Dienstleister. In dieser Broschüre werden mögliche Potenziale im Bereich der Elektromobilität aufgezeigt. Die Mobilität der Zukunft ist eine interdisziplinäre Angelegenheit und kein reines Automotive-Thema mehr. Beispiele wie Mobilitätsmanagement, eCommerce und Individualisierung sind im Mobilitätsbereich für die IT-Branche relevant.
Die Informationsbroschüre "Konzept für einen spielerischen Ansatz zur multimodalen Mobilitätsplanung“ richtet sich an Spiele- und System-Designer sowie Entwickler. In dieser Broschüre werden mögliche Potenziale im Bereich des allgemeinen Mobilitätsmanagements aufgezeigt, Automobilhersteller vernetzten sich zunehmend mit Technologie-Unternehmen.
Die Informationsbroschüre „Anforderungen an die Gestaltung multimodaler Mobilitätsanwendungen“ richtet sich an IT-Dienstleister. In dieser Broschüre werden mögliche Potenziale im Bereich des allgemeinen Mobilitätsmanagements aufgezeigt. Automobilhersteller vernetzten sich zunehmend mit Technologie-Unternehmen. Es geht nicht nur um die besondere Entwicklung von spezieller Elektronik- und Softwarelösungen für Navigations- und Entertainmentsysteme oder auch Fahrassistenz-Systemen in modernen PKW, sondern um einen übergreifenden Design- und Interaktionsansatz für miteinander vernetzte Geräte.
RGB-D sensors such as the Microsoft Kinect or the Asus Xtion are inexpensive 3D sensors. A depth image is computed by calculating the distortion of a known infrared light (IR) pattern which is projected into the scene. While these sensors are great devices they have some limitations. The distance they can measure is limited and they suffer from reflection problems on transparent, shiny, or very matte and absorbing objects. If more than one RGB-D camera is used the IR patterns interfere with each other. This results in a massive loss of depth information. In this paper, we present a simple and powerful method to overcome these problems. We propose a stereo RGB-D camera system which uses the pros of RGB-D cameras and combine them with the pros of stereo camera systems. The idea is to utilize the IR images of each two sensors as a stereo pair to generate a depth map. The IR patterns emitted by IR projectors are exploited here to enhance the dense stereo matching even if the observed objects or surfaces are texture-less or transparent. The resulting disparity map is then fused with the depth map offered by the RGB-D sensor to fill the regions and the holes that appear because of interference, or due to transparent or reflective objects. Our results show that the density of depth information is increased especially for transparent, shiny or matte objects.