MobileRGBD

MobileRGBD is corpus dedicated to low level RGB-D algorithms benchmarking on mobile platform. We reversed the usual corpus recording paradigm. Our goal is to facilitate ground truth annotation and reproducibility of records among speed, trajectory and environmental variations. As we want to get rid of unpredictable human moves, we used dummies in order to play static users in the environment. Interest of dummies resides in the fact that they do not move between two recordings. It is possible to record the same robot move in order to evaluate performance of detection algorithms varying speed. This benchmark corpus is intended for "low level" RGB-D algorithm family like 3D-SLAM, body/skeleton tracking or face tracking using a mobile robot.

MobileRGBD是专用于移动平台底层RGB-D算法基准测试的语料库。我们打破了常规语料库的录制范式，旨在简化真值标注流程，并提升不同速度、轨迹与环境变化下录制结果的可复现性。为规避不可预测的人工移动带来的干扰，我们采用人形假人模拟环境中的静态使用者。人形假人的优势在于，其在两次录制过程中不会发生位置移动。我们可录制完全一致的机器人运动轨迹，以此评估检测算法在不同速度下的性能表现。该基准测试语料库面向基于移动机器人的底层RGB-D算法族，例如3D-SLAM、人体/骨骼追踪或人脸追踪算法。