Non-line-of-sight (NLOS) tracking has drawn increasing attention in recent
years, due to its ability to detect object motion out of sight. Most previous
works on NLOS tracking rely on active illumination, e.g., laser, and suffer
from high cost and elaborate experimental conditions. Besides, these techniques
are still far from practical application due to oversimplified settings. In
contrast, we propose a purely passive method to track a person walking in an
invisible room by only observing a relay wall, which is more in line with real
application scenarios, e.g., security. To excavate imperceptible changes in
videos of the relay wall, we introduce difference frames as an essential
carrier of temporal-local motion messages. In addition, we propose PAC-Net,
which consists of alternating propagation and calibration, making it capable of
leveraging both dynamic and static messages on a frame-level granularity. To
evaluate the proposed method, we build and publish the first dynamic passive
NLOS tracking dataset, NLOS-Track, which fills the vacuum of realistic NLOS
datasets. NLOS-Track contains thousands of NLOS video clips and corresponding
trajectories. Both real-shot and synthetic data are included. Our codes and
dataset are available at this https URL

本研究提出了一种纯被动式的非直射式跟踪方法，仅通过观察一个继电器墙来追踪走在隐形房间中的人，利用差分帧作为时空局部运动信息的必要携带者，提出了 PAC-Net，填补了现有非直射式数据集的空缺。