Multi-person abnormal behavior detection method based on security monitoring video data

A video data, security monitoring technology, applied in the direction of instruments, character and pattern recognition, computer components, etc.

Active Publication Date: 2016-03-23
ZHONGYUAN WISDOM CITY DESIGN RES INST CO LTD
View PDF4 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the software system based on the visual perception network intelligent environment needs to solve three key interrelated technical problems: one is the multi-camera control model for multi-scale behavior informa

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multi-person abnormal behavior detection method based on security monitoring video data
  • Multi-person abnormal behavior detection method based on security monitoring video data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] Specific embodiments are given below to further describe the present invention in detail.

[0023] A method for detecting abnormal behavior of multiple people based on security monitoring video data, comprising the following steps:

[0024] Step 1: Video Data Acquisition

[0025] Collect the standard AV output signal of the surveillance camera, and compress and encode the collected AV signal to form H.264 and MPEG-4 standard video data;

[0026] Step 2: Pedestrian Feature Extraction

[0027] Aiming at the extraction of pedestrian features, a hierarchical pedestrian detection method is proposed.

[0028] 2.1. First, carry out coarse-level detection, and extract features that can effectively describe the outline of the human body and calculate relatively simple features, Haar features and FDF features for the collected video images, and obtain a coarse-level detector.

[0029] 2.2. Perform traversal detection on the image to be tested, and use the AdaboostCascade metho...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a multi-person abnormal behavior detection method based on security monitoring video data. According to the method, a standard AV output signal of a monitoring camera is acquired; pedestrian characteristics are extracted, and coarse detectors, coarse pedestrian ROIs and precise ROIs are respectively acquired; pedestrian behavior tracking is carried out, a particle filtering method is employed to respectively surround each tracking target of a video into a rectangular frame, a multi-order autoregression process mathematics model is established for state transferring of each tracking target, and a state transferring model for describing actual motion situations of motion targets is acquired; under the particle filtering framework, a particle filtering human body tracking method integrated with color and shape characteristics is acquired; abnormal-pedestrian classification is carried out, and optical flow characteristics of the precise ROIs are calculated; each frame of gray-scale image in the monitoring video flow is set to be a Markov random field ; characteristics of pedestrians determined to have abnormal traffic behaviors in video monitoring scenes are extracted, a continuous hidden Markov model is established, and the abnormal behaviors are identified.

Description

technical field [0001] The invention relates to a multi-person abnormal behavior detection method based on security monitoring video data, which belongs to the field of 3S integration application. Background technique [0002] Perception and recognition of human behavior in complex environments is one of the hot and difficult topics in intelligent video surveillance research. Its task is to use cameras to perform real-time monitoring and scene interpretation of continuous and transient objects in a specific environment, and to understand and predict context-related objects. Behaviors and events, and interact with observed objects based on information obtained from sensors, are of great value in applications such as detection, monitoring, management, and command in public facilities, commercial, transportation, and military scenarios. The ever-increasing social security requirements have created the need to monitor many environments, making the research and application of vid...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/53G06F18/295
Inventor 陈长宝李传奎杜红民孔晓阳王茹川郭振强王磊
Owner ZHONGYUAN WISDOM CITY DESIGN RES INST CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products