We present our system for automatic lecture recording. In contrast to traditional lecture recording systems our approach aims to imitate a real camera team, consisting of multiple cameramen and a director, in order to make the recording more vivid. At first, we introduce the environment. Then, we present our approach, beginning with the director module, followed by the cameraman module and the sensor tools module, referring to the jobs of the respective human originals. The director is based on an Extended Finite State Machine, with transition conditions depending on input from sensor tools. The cameraman automatically controls iris, focus, etc., and also takes basic cinematographic rules into account. The video concludes with an example result of our virtual camera team of a real lecture. A video demo of our approach is available at [4].

A large number of videos cannot be visualized on mobile devices (e.g.,PDAs or mobile phones)due to an inappropriate color depth of the displays. Important details are lost if the color depth is reduced. A major challenge is the preservation of the semantic content in spite of this fact. In this paper, we present a novel adaptation algorithm to enable the playback of videos on color-limited mobile devices. Dithering algorithms diffuse the error to neighbor pixels and do not work very well for videos. We propose a non-linear transformation of luminance values and use textures in combination with edges to reduce the color depth in videos.

A large number of previously recorded videos cannot be directly visualized on mobile devices like PDAs or mobile phones due to an inappropriate screen resolution of their displays. Transcoding can be used to change the resolution, however, the usual transcoding algorithms have problems preserving the semantic content. For instance, superimposed text is unreadable if the character size drops below a certain value. In this paper, we present a novel adaptation algorithm to scale and crop videos while preserving their semantic content. Semantic features in a shot are combined to select a suitable region to be resented in the adapted video.