Crowd Detection System - 2 Pages

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Crowd Detection System

Catalog excerpts

Crowd Analysis is available for a Heavy Crowd of hundreds of people. Quantified Crowd Density Levels - Graph Graph of Transition of Crowd Density Levels Fast video analysis and processing few seconds after video taking ) Analyzes videos from surveillance cameras, quantifies crowd density levels and displays results on staffs' PCs and the Information Boards for customers. Video Analysis Solution for Crowd Monitoring and Management Crowd Detection System • NEC's New Digital Security Solution to grasp Real-Time Crowd Density Levels and People Number using video surveillance systems. • It powerfully assists you to clarify the crowd density levels and crowd behavior which are the keys to the crowd management. NEC's crowd behavior analysis technology provides you more precise information on crowd density levels with quantified data including the number of people and the percentage of crowd density. Videos from Surveillance Cameras Using existing cameras and digital surveillance systems Installable in the system with cameras/ servers of lower performances and narrow bandwidth, as the frame rate and video resolution required for analysis are quite lower. Quantified Crowd Density Levels Gauge, Heat Map, Crowd Flow Line Queue Time Estimation (Optional) Estimates wait times from the crowd density levels analyzed/ number of people counted. Displays real-time information of crowd density including estimated queue times on staffs' PCs (updated in every 1-2 seconds) and the Information Boards for customers (updated in every 1 min). (Traffic Line)

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Crowd Detection System Key Features and Benefits NEC’s unique and robust Crowd Behavior Analysis Engine  NEC’s Crowd Behavior Analysis Technology handles a mass of people as a single object, not as a group of individuals. As it won’t detect, track and identify each individual person, it requires no personal data for video analysis.  It enables counting the number of people in a larger group and where people’s figures are overlapped in an image.  Provides data of the specified and the entire areas in an image. Case Study Case Study 1 - Railway Station, Airport, Bus Terminal, Stadium,...

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