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In a non-professional environment, multi-camera recordings of theater performances or other stage shows are difficult to realize, because amateurs are usually untrained in camera work and in using a vision mixing desk that mixes multiple cameras. This can be remedied by a production process with high-resolution cameras where recordings of image sections from long shots or medium-long shots are manually or automatically cropped in post-production. For this purpose, Gandhi et al. presented a single-camera system (referred to as Gandhi Recording System in the paper) that obtains close-ups from a high-resolution recording from the central perspective. The proposed system in this paper referred to as “Proposed Recording System” extends the method to four perspectives based on a Reference Recording System from professional TV theater recordings from the Ohnsorg Theater. Rules for camera selection, image cropping, and montage are derived from the Reference Recording System in this paper. For this purpose, body and pose recognition software is used and the stage action is reconstructed from the recordings into the stage set. Speakers are recognized by detecting lip movements and speaker changes are identified using audio diarization software. The Proposed Recording System proposed in this paper is practically instantiated on a school theater recording made by laymen using four 4K cameras. An automatic editing script is generated that outputs a montage of a scene. The principles can also be adapted for other recording situations with an audience, such as lectures, interviews, discussions, talk shows, gala events, award ceremonies, and the like. More than 70 % of test persons confirm in an online study the added value of the perspective diversity of four cameras of the Proposed Recording System versus the single-camera method of Gandhi et al.

A production process using high-resolution cameras can be used for multi-camera recordings of theater performances or other stage performances. 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. Measured are differences on average up to 0.3 seconds. 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 novel model, a more human appearance can be given to otherwise exact and robotic cuts, when automating image cuts.