Personnel attribute recognition

By obtaining surveillance videos through front-end cameras, calibrating them through frames, and triggering attribute recognition when pedestrians enter the area, it can be used for various purposes such as crowd classification statistics or abnormal alarms. It can recognize 14 common attribute categories, including gender, age group, top with logo, top type, top color, bottom type, bottom color, body orientation, wearing masks, hats, wearing glasses, backpack type, hair length, and whether to hold items.

• Strict selection algorithm
• Human related
• Large property management