High-density target capture is a specialized capability designed for scenarios with high pedestrian traffic, such as urban squares or station exits, where crowd density can exceed 100 person-times in a single frame. This feature ensures accurate trajectory generation and optimal snapshots without missed or false captures in challenging environments. The technical architecture of this feature is built upon three fundamental pillars, as the system requires that high-density target capture enabled by: object detection algorithm and target trajectory generation algorithm + chip computing power + large-capacity memory .

Hardware requirements are particularly stringent, necessitating a professional AI chip, such as a 4 TOPS NPU, to manage the processing load of tracking up to 200 targets per frame. Large- capacity memory, typically 4 GB of DDR, is also vital to ensure an ultra-low snapshot repetition rate of less than 8%. While high-frequency exposure—specifically T-Shot double-exposure technology—is an advanced imaging technique used to capture clear snapshots of vehicles and targets simultaneously at night, it is a distinct imaging enhancement rather than a prerequisite for the high-density capture logic itself. High-frequency exposure focuses on resolving illumination and motion blur, whereas high-density capture focuses on the computational capacity to detect and track a massive volume of objects.