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A crowd safety evaluation method based on crowd density and pedestrian speed

A technology of crowd density and safety level, which is applied in the direction of reasoning method, character and pattern recognition, image data processing, etc. It can solve the problems of low accuracy, no clear warning level, and inability to effectively count the crowd density in predetermined areas, so as to improve the application High performance, reasonable design and simple operation

Inactive Publication Date: 2018-12-25
YANSHAN UNIV
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Problems solved by technology

However, this method cannot effectively count the population density in the predetermined area, there is no clear warning level, and the accuracy of early warning is low

Method used

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  • A crowd safety evaluation method based on crowd density and pedestrian speed
  • A crowd safety evaluation method based on crowd density and pedestrian speed
  • A crowd safety evaluation method based on crowd density and pedestrian speed

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Embodiment Construction

[0034] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0035] A crowd safety assessment method based on the crowd density and pedestrian speed of the present invention, firstly, preprocess the acquired video frame images, obtain the feature vector T of the crowd image features through the background difference method, and then input the feature vector T to the neural network The network performs regression to obtain the crowd density and its changing law in the scene. Further, the optical flow method is used to calculate the pedestrian speed. The crowd density and pedestrian speed in the scene are selected as the evaluation factors of the fuzzy reasoning system, and the crowd safety evaluation is obtained through the fuzzy reasoning knowledge base and defuzzification.

[0036] Such as figure 1 , figure 2 As shown, the evaluation method includes the following steps:

[0037] Step 1: Obtain vide...

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Abstract

The invention discloses a crowd safety degree evaluation method based on crowd density and pedestrian speed, which comprises the following contents: adopting a neural network model regression to predict the crowd density by using a feature vector composed of a foreground area and a perimeter of the obtained video frame image; based on an LK optical flow improved pyramid Lucas-Kanade optical flow algorithm, processing continuous image frames to obtain the pedestrian velocity, i.e. the average velocity of individual pedestrians; constructing a fuzzy inference system to evaluate the crowd safetygrade: selecting evaluation factors and determining its membership function; establishing crowd attributes and a safety risk rule base, and carrying on fuzzy reasoning on the input according to the rule base; defuzzifying the reasoning results, and then evaluating the risk level of crowd safety. The invention establishes a mathematical model for crowd density, pedestrian speed and output crowd safety risk grade, and adopts a fuzzy inference method to determine the influence of each element of crowd attributes on the early warning grade, which is reasonable in design and simple in operation, and improves practical applicability.

Description

technical field [0001] The invention relates to the field of video analysis and public safety, in particular to a method for evaluating crowd safety degree based on crowd density and pedestrian speed. Background technique [0002] Crowd density is a prominent feature of modern large-scale activities, and the safety problems caused by dense crowds are also a focus of safety management for large-scale activities. Under normal circumstances, a large number of people gather will not cause accidents, but due to the failure to achieve effective early warning and control when unexpected accidents occur, it often causes relatively large casualties. For example, at 23:35 on December 31, 2014, at the pedestrian walkway stairs leading to the viewing platform of Huangpu River from Chen Yi Square on the Bund of Shanghai, someone lost balance and fell, causing crowds to stampede, killing 36 people and injuring 49. The above-mentioned incidents resulted in tragedies due to the failure to ...

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Application Information

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IPC IPC(8): G06K9/00G06N5/04G06T7/11G06T7/13G06T7/246G06T7/254
CPCG06N5/048G06T7/11G06T7/13G06T7/246G06T7/254G06T2207/10016G06T2207/30196G06T2207/30232G06V20/53
Inventor 胡硕刘乃成杨哲
Owner YANSHAN UNIV
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