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Real-time bus passenger flow volume statistical method

A statistical method and technology of passenger flow, applied in the field of pattern recognition, which can solve the problems that the optical flow field distribution is not very reliable and accurate, and the optical flow field calculation is time-consuming.

Inactive Publication Date: 2010-07-14
HUAZHONG UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to noise, multiple light sources, shadows, transparency, and occlusion, the calculated optical flow field distribution is not very reliable and accurate.
At the same time, the calculation of the optical flow field is also very time-consuming.

Method used

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  • Real-time bus passenger flow volume statistical method

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Embodiment Construction

[0051] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0052] figure 1 It is the implementation flowchart of this embodiment, including several steps of target detection, target tracking, target behavior analysis and passenger flow counting. When analyzing images, this embodiment only utilizes the brightness information of the image (ie grayscale image).

[0053] In the target detection step, the following processes are included:

[0054] 1. Extract the target prior gray statistical histogram.

[0055] The histogram is a function of the statistical characteristics of each gray value of the image and the gray value of the image. It counts the number or probability of each gray level in an image. First, manually extract multiple images containing only passenger head area information from the pre-captured passenger flow video images to form a target sample set; then extract the grayscale statistic...

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Abstract

The invention provides a real-time bus passenger flow volume statistical method based on a target prior distribution, which adopts the methods of target detection, target tracking, target behavioral analysis and the like, and belongs to the technical field of pattern recognition. The method concretely comprises the following steps: utilizing the target prior grayscale to do statistics of the back-projection operation of a histogram on an input video image, and then performing the treatment of difference, binaryzation, wave filtering, connected domain marking and the like on a back-projection image to realize the target detection; adopting the grayscale to interrelate, match and track and a mean translation algorithm to search and track so as to realize the accurate positioning of the target; and finally analyzing the motion trail of the target to judge the get on or off of passengers, and realizing the passenger flow volume statistics. The invention can provide fine-grained reliable basis for a public transit company to realize intelligent dispatching of buses, audience analysis of the mobile media advertising of the busses and the like.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a method for real-time bus passenger flow statistics. Background technique [0002] With the rapid development of the global economy, various demands for transportation have increased significantly, and the connection between transportation and social and economic life has become increasingly close. Data, thereby reducing the use of buses and improving the safety of road traffic. Therefore, the development of vehicle-mounted mobile value-added services that can improve the current driving environment has become an urgent need for the harmonious development of my country's economy and society. Bus passenger flow statistics is one of them. By obtaining the passenger flow of the road section in real time during this period, the bus company can more reasonably schedule the bus. On the other hand, the bus advertising investor can also conduct a detailed analysis...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 桑农陈景东黄朝露刘乐元罗大鹏唐奇玲高常鑫王海王强李驰
Owner HUAZHONG UNIV OF SCI & TECH
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