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 robotic lower-limb exoskeletons and prostheses. However, inadequate and private training datasets have impeded the widespread development and dissemination of image classification algorithms for 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 both 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 communal platform for training, developing, and comparing image classification algorithms (e.g., convolutional neural networks) for next-generation environment recognition systems. Beyond the 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：计算机视觉与人工智能领域的近期进展，助力研究者开发出适用于机器人下肢外骨骼与假肢的环境识别系统。然而，训练数据集存在的规模不足与隐私性约束，分别掣肘了环境识别相关图像分类算法的大规模开发与推广应用。为解决上述缺陷，我们构建了ExoNet——首个开源的大规模分层式人类行走环境可穿戴相机图像数据库。该数据库在规模与多样性方面均处于领先水平，包含超过560万张涵盖真实室内外行走环境的图像，采集工作通过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，为下一代环境识别系统的图像分类算法（如卷积神经网络）的训练、开发与对比提供了前所未有的公共平台。除下肢外骨骼与假肢的控制场景外，ExoNet的应用范围还可拓展至人形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：人类行走环境可穿戴相机图像集. 正在审稿中。