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Crowd exceptional event detection method based on LBP (Local Binary Pattern) weighted social force model

A technology of social force model and detection method, applied in computer parts, character and pattern recognition, image data processing, etc., can solve complex problems, achieve good time domain characteristics and density characteristics, good pedestrian movement, and reduce complexity Effect

Active Publication Date: 2012-09-19
联通(上海)产业互联网有限公司
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

"However, this patent still has the above-mentioned background modeling, foreground extraction, and target detection and tracking, which are relatively complicated.

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  • Crowd exceptional event detection method based on LBP (Local Binary Pattern) weighted social force model
  • Crowd exceptional event detection method based on LBP (Local Binary Pattern) weighted social force model
  • Crowd exceptional event detection method based on LBP (Local Binary Pattern) weighted social force model

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Embodiment

[0036] The video sequence used in this implementation comes from a crowd abnormal event sequence at the University of Minnesota. The video contains two scenes, indoor and outdoor. The crowd in each video begins to disperse in all directions after a period of normal walking. In this article, the event of crowd dispersal is defined as abnormal crowd behavior that needs to be detected. Among them, the indoor scene uses 548 frames for training and 893 frames for experimental result verification; the outdoor scene uses 802 frames for training and 675 frames for experimental result verification.

[0037] The method for detecting abnormal crowd events based on the LBP weighted social power model involved in this embodiment, the overall process is as follows figure 1 As shown, including the following specific steps:

[0038] Step 1: Calculate the optical flow vector of the sampling point based on the block matching method.

[0039] First, the color video is converted into gray-scale video...

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Abstract

The invention discloses a crowd exceptional event detecting method based on an LBP (Local Binary Pattern) weighted social force model. The method comprises the following steps of: computing a light stream vector of a sampled point based on a block-matching method; extracting dynamic textures of the sampled point by a time-space domain local binary pattern, and performing spectral analysis of Fourier transform; computing social force of the sampled point based on LBP weighted social force model; performing histogram quantization on the social force and performing classification on the video sequence based on a support vector machine to detect the exceptional behavior. Through combination of light stream and LBP frequency spectrum, the method provided by the invention innovatively calculates the social force to detect the exceptional behavior of the crowd, thus avoiding background modeling, prospect detection and detection and track of target, improving robustness and reduce calculated amount, and being particularly fit for occassions with large density of the crowd and complicated environment.

Description

Technical field [0001] The invention relates to the technical field of computer video processing, in particular to a crowd abnormal event detection method based on an LBP weighted social force model, and is particularly suitable for abnormal behavior detection with high crowd density and complex scenes. Background technique [0002] With the development of society and the continuous increase of population, casualties caused by emergencies in large-scale crowd activities have aroused people's attention to social public safety issues, and more and more video surveillance systems have been used in various public places. Traditional video surveillance systems use closed-circuit televisions to monitor scenes to manually monitor and alarm, which is time-consuming, laborious and lacks objectivity. With the continuous expansion of the surveillance system and the rapid growth of video data, it is difficult for limited manpower to obtain useful information from the massive surveillance vid...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06T7/20
Inventor 杨华曹艺华张科铭苏航
Owner 联通(上海)产业互联网有限公司
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