1. People counting script is able to accurately quantify the number of people by the defined zones
2. Accurate real-time metrics were obtained. The accuracy can be modified by changing the threshold.
A growing challenge in retail, public venues, and event spaces is accurately monitoring the number of individuals within different zones of a particular area. This information is crucial for managing crowd control, optimizing space utilization, and ensuring security and safety compliance. Traditionally, these tasks have been carried out manually, requiring significant human labor, and are prone to error and inconsistency.
There is a pressing need for a scalable, reliable, and accurate solution capable of performing this task with minimal human intervention. Given the advancements in video surveillance technology and computer vision techniques, developing an automated solution that can perform real-time people counting by zone in video footage is an achievable goal.
A computer vision-based solution for people counting by zone in video could be achieved through the following approach:
Video Acquisition and Preprocessing: High-definition video feeds from strategically placed cameras capture images of the area of interest. The feeds are then preprocessed to improve the quality and remove noise. This step might include processes like frame differencing, background subtraction, and image thresholding.
Zone Definition: Each area monitored by a camera is divided into predefined zones. This process could involve manual setup or an automated process based on specific criteria like floor space, distance markers, etc.
Human Detection and Segmentation: This involves the identification and extraction of human figures from the video frames. This is usually achieved using a trained deep learning model, such as a Convolutional Neural Network (CNN) or a pre-trained model like YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), or Faster R-CNN.
Object Tracking: Once individuals are detected, they need to be tracked as they move across frames and potentially across zones. This can be achieved using tracking algorithms like the Kalman filter or Multiple Object Tracking (MOT) techniques.
People Counting: For each detected person, the system assigns an ID, which is used to keep count as people enter, stay within, or exit a zone. This step might involve methods to handle occlusion (where people are hidden behind other people or objects) to prevent undercounting.
Data Analysis and Reporting: The counting data can be aggregated and analyzed to generate real-time reports. The system can provide visual representations of the data, showing the count of people in each zone at any given time.
Business Owners/Operators: Business owners or operators of venues, retail stores, or event spaces have a significant stake in people counting by zone. Accurate and real-time information about crowd distribution helps them optimize space utilization, improve customer flow, and enhance overall operational efficiency. It allows them to make informed decisions regarding resource allocation, staffing, and crowd management strategies.
Security Personnel: Security personnel are responsible for ensuring the safety and security of the premises and its occupants. People counting by zone helps them monitor crowd density, detect potential security threats, and manage emergency situations more effectively. It enables them to allocate security resources appropriately and maintain a safe environment for everyone.
Event Organizers: Event organizers rely on accurate people counting to plan and execute successful events. By tracking crowd numbers in different zones, they can ensure compliance with occupancy limits, maintain crowd control, and enhance the overall event experience. Real-time information about crowd distribution enables them to make timely adjustments to the event layout, staffing, and logistics.