Counting method based on pedestrian head and shoulder multi-target detecting and tracking

Abstract

The invention relates to a counting method based on pedestrian head and shoulder multi-target detecting and tracking. The method comprises the steps that a positive sample data set and a negative sample data set of a pedestrian head and shoulder image are constructed, HOG feature vectors of the data sets are extracted, moving foregrounds are extracted through a Gaussian mixture model, the minimum envelope rectangle of the foregrounds is taken as a detection region, pedestrian head and shoulder targets are detected through a multi-scale slide window and a trained SVM classifier, a target matching matrix is initialized into a zero matrix, a pedestrian counter is initialized, the number of the target people passing through the area is counted, and for a target in a tracking list TraList, if the center position of the target is located out of a tracking area, the target is deleted, and the pedestrian counter is updated. According to the method, the pedestrian volume in the specific area is counted through a computer vision technology, the method is used for pedestrian counting, the problems that traditional pedestrian counting is low in efficiency and accurate rate are solved, the digital and intelligent level of pedestrian counting is increased, and the method is a multi-win project capable of bringing the economic benefit and social security and is suitable for multiple indoor and outdoor scenes.

Description

technical field [0001] The invention belongs to the technical field of intelligent monitoring, in particular to a statistical method based on pedestrian head and shoulder multi-target detection and tracking, which uses computer vision technology to count the flow of people in a specific area. Background technique [0002] At present, pedestrian counting has a wide range of commercial applications, such as stations, tourist attractions, exhibition areas, commercial streets, etc. Using the statistics of the number of people, it is possible to effectively carry out personnel mobilization, resource allocation and provide better security. In addition to the traditional manual counting, the current common pedestrian counting methods mainly include mechanical transmission gates, infrared induction counting and computer vision. Due to the limitation of hardware conditions, gate and infrared sensor counting are only suitable for indoor environments with less traffic and depend on th...

AI Technical Summary

Problems solved by technology

[0003] To sum up, there are the following deficiencies in the current technical scheme of people flow counting: (1) the camera counting the number of pedestrians using a vertically downward camera is generally only suitable for indoor environments; (2) in environments with complex pedestrian movement directions, The effective moving pixel blocks of the cross-section counting blocks may interfere with each other, resulting in low pedestrian counting accuracy; (3) Due to the non-rigidity of pedestrian posture, environmental noise and occlusion problems during pedestrian movement, tracking cannot be detected in every frame target, it is easy to cause target tracking loss;

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