The 3D-video Point Cloud Musicians Dataset

DESCRIPTION The 3D-video Point Cloud Musicians Dataset provides 3D-video point clouds of several performers playing five different instruments: cello, doublebass, guitar, saxophone, and violin. The full 3D-video recordings span 1 hour of duration with an average of 12 different performers for each instrument. All musicians point clouds are centered in the origin and the axes have the following meaning: the body face direction is the z-axis, stature direction is the y-axis, and the side direction is the x-axis. The provided musician point clouds are down-sampled from their full resolution by using a voxel size of 0.01. RECORDINGS Recordings were conducted using a single Azure Kinect DK placed one meter above the floor and capturing a frontal view of the musician at a distance of two meters. The Azure Kinect DK depth camera was capturing a 75°x65° field of view with a 640x576 resolution while the Azure Kinect DK color camera was capturing with a 1920x1080 resolution. Both cameras were recording at 15 fps and Open3D library was then used to align depth and color streams and generate a point cloud for each frame. Each frame is saved as .ply format file. NAMING CONVENTION The folders in the dataset follow this structure: Instrument -> Person. The captured frames are named according to their temporal position using five numerical characters, i.e. %5d.ply

数据集描述
3D视频点云音乐人数据集（3D-video Point Cloud Musicians Dataset）收录了多位演奏者演奏5种不同乐器时的3D视频点云，涵盖乐器包括大提琴、低音提琴、吉他、萨克斯与小提琴。完整3D视频录制总时长达1小时，每种乐器平均对应12位不同演奏者。所有音乐人点云均以原点为中心，坐标轴定义如下：人体正面朝向为z轴，身高方向为y轴，侧向为x轴。本次提供的音乐人点云均通过体素尺寸为0.01的降采样操作，从原始高分辨率点云生成。

录制信息
本次录制采用单台Azure Kinect DK设备完成，设备安装于离地1米高度，以2米距离采集演奏者的正面画面。该设备的深度相机采集分辨率为640×576，视场角为75°×65°；彩色相机采集分辨率为1920×1080。两台相机均以15 fps帧率录制，后续通过Open3D库对齐深度与彩色数据流，并为每一帧生成点云。每一帧均以.ply格式文件存储。

命名规范
数据集中的文件夹遵循如下层级结构：乐器目录 → 演奏者目录。采集得到的帧根据其时间位置命名，采用5位数字格式，即%5d.ply。

搜集汇总

背景与挑战

背景概述

该数据集是一个3D视频点云数据集，专注于音乐表演者，涵盖五种乐器（大提琴、低音提琴、吉他、萨克斯管、小提琴），总时长为1小时，每种乐器平均有12名表演者。数据通过Azure Kinect DK设备录制，生成的点云经过下采样处理，每帧以.ply格式保存，适用于3D计算机视觉和动作分析研究。