product feature

• Deep learning algorithm is adopted, based on massive pictures and video resources, and target features are extracted by the machine itself to form deep learnable human clothing images and identify them
• Based on pedestrian trajectory analysis, the entry and departure of target personnel in the specified scene are counted, and the passenger flow is counted
• On the basis of passenger flow, it also supports clothing mode or face mode switch: clothing mode: 1. Support human body comparison and attribute weight removal, filter custom clothing and attribute passenger flow count; 2. Support the classification of human attributes, including: gender, age, carrying things, hats (helmets), masks
• Face mode: Support face capture, Angle filtering, face attribute classification, support for dynamic deweighting based on face comparison
• Event alarm function: Support motion detection, occlusion alarm, hard disk full, hard disk error, network disconnection, IP address conflict, illegal access, abnormal restart
• Support the standard 256 GB MicroSD/MicroSDHC/MicroSDXC card storage, support 10 M / 100 M / 1000 M adaptive front-end ports
• Support open network video interface, ISAPI, GB/T28181-2016, ISUP5.0, video library
• Supports three-level user rights management, authorized users and passwords, and IP address filtering

applicable scene

Suitable for exhibition halls, exhibition halls, scenic spots, squares, stations, airports, public transportation and other outdoor scenes.

technical parameters