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Pedestrian's abnormal behavior detection method

A detection method and pedestrian technology, applied in image data processing, instruments, character and pattern recognition, etc., can solve problems such as low efficiency and complicated process, and achieve the effect of avoiding the process of model learning, improving efficiency and saving manpower

Active Publication Date: 2016-11-23
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] It can be seen that most of the current abnormal behavior detection methods of pedestrians need to establish a model, and then carry out model learning, which is inefficient and complicated

Method used

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  • Pedestrian's abnormal behavior detection method
  • Pedestrian's abnormal behavior detection method

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Experimental program
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Effect test

Embodiment 1

[0038] Step S22, calculating the number of blocks included in the tracked group within a certain period of time, detecting whether there is any abnormality according to the threshold and weight, and updating the detection threshold.

[0039] During the group tracking process, the group structure of the group will change dynamically as the number of people in the group changes, and the number of blocks contained in the group composed of blocks will also change accordingly. Therefore, the abnormal behavior of the group, which is a large change in the number of groups, can be detected through the number of blocks contained in the group. The specific process is as follows:

[0040]Since the population structure changes little in adjacent frames and the number of blocks contained in the population is relatively stable, so every m frames, the number of blocks contained in the tracked population is calculated by the function f. Wherein, the function f may be the variance of the bloc...

Embodiment 2

[0042] Step S23, according to the group synergy value of each frame of the tracked group, calculate the group synergy value of the group within a certain period of time, and judge whether there is abnormal behavior according to the preset threshold. Specific steps are as follows:

[0043] At intervals of d frames, the group synergy value of the group in the d frame is calculated by the function φ. In specific calculation, the function φ can average the group synergy value of the group in the d frame, or calculate the variance. Then make a difference with the φ value of the previous d frame, when the difference is greater than the preset threshold T, that is, φ n -φ n-1 When >T, it is judged that an abnormality has occurred. If the difference is smaller than the preset threshold T, the above process is repeated until the group tracking ends. If the difference is still smaller than the preset threshold until the entire tracking process of the group is completed, it is judged ...

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Abstract

The invention relates to a pedestrian's abnormal behavior detection method comprising the steps as follows: estimating the pedestrian density in a video frame, and classifying the video frame as a high- and medium-density scene or a low-density scene according to the obtained pedestrian density; if the video scene is a high- and medium-density scene, grouping-tracking the pedestrians in the video frame and detecting whether there is an abnormal behavior using a group tracking method based on group structure dynamic evolution; and if the video scene is a low-density scene, tracking a target pedestrian in the video frame and detecting whether there is an abnormal behavior using a trajectory segment correlation method. The method is simple and convenient, avoids a complex model learning process, is of strong adaptability, and enables the monitoring staff to find the cause of a security problem more efficiently and saves manpower.

Description

technical field [0001] The invention relates to a method for detecting abnormal behavior of pedestrians. Background technique [0002] In recent years, as security issues have received increasing attention from society, abnormal behavior detection in videos has become more and more important. Inconsistent with the behavior of the surrounding pedestrians, there are wandering or lingering behaviors, and these behaviors may cause some safety problems. By analyzing the surveillance video, and then judging some abnormal behaviors that cause security problems, a large amount of information that is useless to security in the surveillance video can be filtered out, saving a lot of manpower. [0003] At present, due to the large size and density of the crowd, the abnormal behavior of the group is mostly studied from a macro perspective, that is, the group is studied as a whole. The main steps are as follows: detection and tracking of video moving objects; crowd monitoring according...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T7/20
Inventor 董露李娜冯良炳
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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