ExoNet Database: Wearable Camera Images of Human Locomotion Environments

Abstract: Recent advances in computer vision and artificial intelligence are allowing researchers to develop environment recognition systems for powered lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for classifying human walking environments. To address these limitations, 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 contains 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 923,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through IEEE DataPort, ExoNet offers an unprecedented communal platform to train, develop, and compare next-generation image classification algorithms for human locomotion environment recognition. Besides the control of powered lower-limb exoskeletons and prostheses, prospective 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. Frontiers in Robotics and Artificial Intelligence. Under Review.

摘要：近年来计算机视觉与人工智能领域的最新进展，使得研究人员得以研发面向动力下肢外骨骼与假肢的环境识别系统。然而，小规模且私有化的训练数据集，阻碍了用于识别人类行走环境的图像分类算法的广泛开发与推广应用。为解决上述局限，我们构建了ExoNet——首个开源、大规模的分层式人类行走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无可比拟，包含超560万张不同室内外真实行走环境的图像，这些图像由轻量化可穿戴智能手机相机系统在夏、秋、冬三季采集完成。ExoNet中约92.3万张图像采用12类分层标注架构完成人工标注。该数据集可通过IEEE DataPort公开获取，为训练、开发及对比用于人类行走环境识别的下一代图像分类算法提供了前所未有的公共平台。除应用于动力下肢外骨骼与假肢的控制之外，ExoNet的潜在应用场景还可拓展至人形机器人与自主腿部机器人领域。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. 《Frontiers in Robotics and Artificial Intelligence》，处于审稿阶段。