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Method for detecting crowded people flow in real time based on three-dimensional depth map data

A real-time detection and depth map technology, applied in image data processing, image analysis, instruments, etc., can solve the problem of increasing false detection, and achieve the effect of reducing mutual occlusion, low computational complexity, and simplifying scene complexity

Inactive Publication Date: 2015-08-12
SHANGHAI INST OF MICROSYSTEM & INFORMATION TECH CHINESE ACAD OF SCI
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Problems solved by technology

[0003] With the development of computer vision, methods for counting people based on video and image processing have been proposed, but the existing methods are all processed in two-dimensional images. Scenarios where false positives increase

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  • Method for detecting crowded people flow in real time based on three-dimensional depth map data
  • Method for detecting crowded people flow in real time based on three-dimensional depth map data
  • Method for detecting crowded people flow in real time based on three-dimensional depth map data

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Embodiment Construction

[0027] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0028] Embodiments of the present invention relate to a method for real-time detection of dense crowd flow based on three-dimensional depth map data, such as figure 1 shown, including the following steps:

[0029] (1) Use the camera to obtain the three-dimensional depth map data, wherein, such as figure 2 As shown, the camera is perpendicular to the ground for overhead shooting.

[0030] (2) Preprocessing the collected 3D d...

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Abstract

The invention relates to a method for detecting a crowded people flow in real time based on three-dimensional depth map data. The method comprises the following steps: acquiring three-dimensional depth map data by using a camera; acquiring preliminary head targets by using foreground extraction and head target area detection; tracking pedestrians and recording the movement loci; and determining the number of the pedestrians and moving direction according to the movement loci. The method performs image processing on a three-dimensional depth map, effectively solves a defect of false detection in two-dimensional image data processing, improves the accuracy of people flow statistics, reduces computation complexity, may detect people flow in real time, and is suitable for intelligent video monitoring field.

Description

technical field [0001] The invention relates to the analysis of human flow in the technical field of computer vision, in particular to a real-time detection method of dense human flow based on three-dimensional depth map data. Background technique [0002] The detection and analysis of human flow has a wide range of applications in the field of video surveillance, especially in public places such as shopping malls, stations, airports, and stadiums. Real-time and accurate statistics of the flow of people is very necessary for public transportation, intelligent security, public safety, business statistics and other fields. [0003] With the development of computer vision, methods for counting people based on video and image processing have been proposed, but the existing methods are all processed in two-dimensional images. Scenarios, false positives will increase. Contents of the invention [0004] The technical problem to be solved by the present invention is to provide a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/20
Inventor 皮家甜谷宇章杜若琪张诚吴修浩魏智
Owner SHANGHAI INST OF MICROSYSTEM & INFORMATION TECH CHINESE ACAD OF SCI
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