ExoNet Database: Wearable Camera Images of Human Locomotion Environments

Abstract: Recent advances in computer vision and artificial intelligence have allowed researchers to develop environment recognition systems for predictive control of lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for human locomotion environment recognition, respectively. To address these shortcomings, we developed “ExoNet” - the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. Unparalleled in scale and diversity, ExoNet comprises over 5.6 million images of different indoor and outdoor real-world walking environments, which were collected using a lightweight wearable smartphone camera system throughout the summer, fall, and winter seasons. Approximately 940,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through the IEEE DataPort repository, ExoNet offers an unprecedented community-based platform for training, developing, and comparing next-generation image classification algorithms for human locomotion environment recognition. Beyond the predictive control of lower-limb exoskeletons and prostheses, applications of ExoNet extend to humanoid and autonomous legged robotics.Reference: Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Under Review.摘要：近年来计算机视觉与人工智能领域的长足进展，使得研究人员得以开发用于下肢外骨骼（lower-limb exoskeletons）与假肢（prostheses）预测控制的环境识别系统。然而，小规模且私有化的训练数据集分别阻碍了人类移动环境识别图像分类算法的广泛开发与推广应用。 为解决上述不足，我们构建了"ExoNet"——全球首个开源、大规模分层式人类移动环境可穿戴相机高分辨率图像数据库。该数据库在规模与多样性上均具备无可比拟的优势，包含超过560万张覆盖不同室内外真实行走环境的图像，数据采集依托轻量化可穿戴智能手机相机系统完成，覆盖夏季、秋季与冬季三个季节。其中约94万张图像采用12类分层标注架构完成人工标注。 "ExoNet"可通过IEEE DataPort仓库公开获取，为面向人类移动环境识别的下一代图像分类算法的训练、开发与对比提供了前所未有的社区共建平台。除下肢外骨骼与假肢的预测控制场景外，"ExoNet"的应用范畴还可拓展至类人机器人与自主足式机器人领域。 参考文献：Laschowski B, McNally W, Wong A, 及 McPhee J. (2020). ExoNet数据库：人类移动环境可穿戴相机图像. 投稿待审