Modeling of an Automatic Vision Mixer With Human Characteristics for Multi-Camera Theater Recordings

Abstract

Laymen are not trained in camera control and how to use a vision mixing desk to switch between different cameras in a video production. Specific training and expert knowledge are required. In the non-professional environment, multi-camera recordings of theater performances or other stage performances are therefore difficult to realize. This can be remedied by a production process with high-resolution cameras from which image sections of long shots or medium long shots are cropped manually or automatically in post-production. One approach to automate the generation of suitable image cuts could be to focus on speaker changes so that the person who is speaking is shown in the generated cut. However, these image cuts can appear static and robotic if they are set too precisely. Therefore, the characteristics and habits of professional vision mixers (persons who operate the vision mixing desk) during the editing process are investigated in more detail in order to incorporate them into an automation process. The characteristic features of five different vision mixers are examined, which were used under almost identical recording conditions for theatrical cuts in TV productions. The cuts are examined with regard to their temporal position in relation to pauses in speech, which take place during speaker changes on stage. It is shown that different professional vision mixers set the cuts individually differently before, in or after the pauses in speech. From the analysis of the image cuts, an approach for a model is developed in which the individual characteristics of a vision mixer can be set. With the help of this model, a more human appearance can be given to otherwise exact and robotic cuts, when automating image cuts.