Method and system based on binocular stereoscopic vision for passenger flow density estimation

Abstract

The invention discloses a method and a system based on binocular stereoscopic vision for passenger flow density estimation. The system comprises binocular parallel cameras, a DSP (Digital Signal Processor), a communication module, a video output module and the like, and the system is adopted for estimating passenger flow density. The method comprises the following steps: (1) calibrating a left camera and a right camera to obtain the internal and external parameters of the left camera and the right camera; calculating the accurate principal point difference of the left camera and the right camera; (2) collecting a left image and a right image in real time and carrying out position correction, and adopting a self-adapting window stereo matching method to obtain a current frame parallax error image; (3) splitting a foreground human body target to obtain a binary foreground human body target image; (4) generating a dimensional mapping image of the foreground human body target; (5) calculating the degree of congestion, and obtaining the density estimation through the non-linear relationship between the degree of congestion and the number of people. The method is independent of the influences of scene illumination change, shadow, perspective effect and blocking, and the system has the characteristics that the equipment is simple and the accuracy rate of the density estimation is high.

Description

technical field [0001] The invention relates to the application field of computer vision technology, in particular to a method and system for estimating passenger flow density based on binocular stereo vision. Background technique [0002] Passenger flow density refers to the density of passenger flow on a plane, which can be represented by the number of passengers per unit area, and is used for passenger flow statistics and management in crowded places such as stations, halls, and squares. At present, in the field of passenger flow statistics, the method based on computer vision has become the main technical means and research hotspot. This type of method is divided into: a method based on monocular vision and a method based on binocular stereo vision. [0003] The method based on monocular vision uses a single camera to capture the scenes of passenger flow, and has steps such as image acquisition, moving target detection, head detection and tracking, and passenger flow st...

AI Technical Summary

Problems solved by technology

However, this type of method is cumbersome to calibrate the camera, and the disparity matching and object segmentation algorithms have a large amount of calculation and low precision. The resulting density estimation system has poor real-time performance and adaptability, and low estimation accuracy.

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