A Synchronized Audio-Visual Multi-View Capture System

TL;DR

This paper introduces a multi-view capture system that synchronizes audio and video signals for studying conversational interactions with high temporal precision.

Contribution

It presents a unified system combining multi-camera and multi-microphone setups with a calibration workflow for scalable, synchronized audio-visual data collection.

Findings

Synchronization performance is quantitatively validated.

Recordings are temporally consistent for detailed conversation analysis.

The system supports repeatable, large-scale data acquisition.

Abstract

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.