Holoscopic 3D Micro-Gesture Database

Holoscopic micro-gesture recognition (HoMG) database was recorded using a holoscopic 3D camera, which have 3 conventional gestures from 40 participants under different settings and conditions. The principle of holoscopic 3D (H3D) imaging mimics fly’s eye technique that captures a true 3D optical model of the scene using a microlens array. For the purpose of H3D micro-gesture recognition. HoMG database has two subsets. The video subset has 960 videos and the image subset has 30635 images, while both have three type of microgestures (classes). Each subset has been divided into three partitions: training set, development set and testing set where there is not overlap between them in term of the subjects. The database has been used for Holoscopic Micro-Gesture Recognition Challenge 2018 (HoMGR 2018) that was held at IEEE Face & Gesture 2018 (FG2018) - Xi'an, China, 15-19th May 2018 (https://fg2018.cse.sc.edu/Challenges.html). The database is now publicly available for wider research communities in the research areas of holoscopic 3D image processing, machine learning for gesture recognition and its application in AR and VR.

霍洛斯全息微动作识别（HoMG）数据库采用霍洛斯三维相机录制，其中包含40名参与者在不同设置和条件下进行的3种传统手势。霍洛斯三维（H3D）成像原理模拟飞眼技术，通过微透镜阵列捕捉场景的真实三维光学模型。针对H3D微动作识别的目的，HoMG数据库分为两个子集。视频子集包含960个视频，图像子集包含30635个图像，两者均包含三种微动作类型（类别）。每个子集均被划分为三个部分：训练集、开发集和测试集，三者之间在受试者方面不存在重叠。该数据库已被用于2018年霍洛斯微动作识别挑战赛（HoMGR 2018），该挑战赛于2018年5月15日至19日在西安举行的IEEE Face & Gesture 2018（FG2018）上举办（https://fg2018.cse.sc.edu/Challenges.html）。目前，该数据库已向更广泛的研究领域开放，供研究霍洛斯三维图像处理、手势识别机器学习及其在增强现实和虚拟现实中的应用的研究社区使用。