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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.23089 |
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| _version_ | 1866910157311574016 |
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| author | Shi, Xiangwei Dorta, Gara de Jong, Ruud Shirekar, Ojas Raman, Chirag |
| author_facet | Shi, Xiangwei Dorta, Gara de Jong, Ruud Shirekar, Ojas Raman, Chirag |
| contents | Multi-view capture systems have been an important tool in research for recording human motion under controlling conditions. Most existing systems are specified around video streams and provide little or no support for audio acquisition and rigorous audio-video alignment, despite both being essential for studying conversational interaction where timing at the level of turn-taking, overlap, and prosody matters. In this technical report, we describe an audio-visual multi-view capture system that addresses this gap by treating synchronized audio and synchronized video as first-class signals. The system combines a multi-camera pipeline with multi-channel microphone recording under a unified timing architecture and provides a practical workflow for calibration, acquisition, and quality control that supports repeatable recordings at scale. We quantify synchronization performance in deployment and show that the resulting recordings are temporally consistent enough to support fine-grained analysis and data-driven modeling of conversation behavior. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_23089 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Synchronized Audio-Visual Multi-View Capture System Shi, Xiangwei Dorta, Gara de Jong, Ruud Shirekar, Ojas Raman, Chirag Computer Vision and Pattern Recognition Multi-view capture systems have been an important tool in research for recording human motion under controlling conditions. Most existing systems are specified around video streams and provide little or no support for audio acquisition and rigorous audio-video alignment, despite both being essential for studying conversational interaction where timing at the level of turn-taking, overlap, and prosody matters. In this technical report, we describe an audio-visual multi-view capture system that addresses this gap by treating synchronized audio and synchronized video as first-class signals. The system combines a multi-camera pipeline with multi-channel microphone recording under a unified timing architecture and provides a practical workflow for calibration, acquisition, and quality control that supports repeatable recordings at scale. We quantify synchronization performance in deployment and show that the resulting recordings are temporally consistent enough to support fine-grained analysis and data-driven modeling of conversation behavior. |
| title | A Synchronized Audio-Visual Multi-View Capture System |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2603.23089 |