Multimodal Concert Video Editing: System Design and Exploratory Evaluation

Editing multi-camera concerts requires coordinated decisions about musical relevance, visual quality and cut timing. We present a modular framework that combines instrument activity from multitrack audio, visible instruments and image sharpness with beat-based timing and probabilistic camera selection. An interpretable scoring model links these components to the choice of views over complete shot intervals. Component tests and an exploratory expert study on a four-camera concert yield mixed assessments across the editing variants. The findings motivate extending local audiovisual relevance with contextual and sequence-level criteria. The architecture provides a basis for testing these extensions and studying how component behaviour affects the quality of complete edits.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.35816
Primary Topic
Video Analysis and Summarization
Type
preprint
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preprint

Multimodal Concert Video Editing: System Design and Exploratory Evaluation

Adrian Kempf, Tim Mangliers, Benjamin Himpel, Lennart Schiweck et al.
arXiv (Cornell University)
Video Analysis and Summarization
preprint

Multimodal Concert Video Editing: System Design and Exploratory Evaluation

Adrian Kempf, Tim Mangliers, Benjamin Himpel, Lennart Schiweck, Moritz Feucht, Michelle Retig
preprint en

Abstract

Editing multi-camera concerts requires coordinated decisions about musical relevance, visual quality and cut timing. We present a modular framework that combines instrument activity from multitrack audio, visible instruments and image sharpness with beat-based timing and probabilistic camera selection. An interpretable scoring model links these components to the choice of views over complete shot intervals. Component tests and an exploratory expert study on a four-camera concert yield mixed assessments across the editing variants. The findings motivate extending local audiovisual relevance with contextual and sequence-level criteria. The architecture provides a basis for testing these extensions and studying how component behaviour affects the quality of complete edits.

arXiv (Cornell University)
Video Analysis and Summarization
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