Target object behavior data acquisition method and device based on videos

Abstract

The invention provides a target object behavior data acquisition method based on videos, comprising: first, playing a pending video; according to a scheduled target recognition algorithm and a target tracking algorithm, identifying and tracking a target object in the video, and according to the corresponding relation between a video pixel coordinate and a physic coordinate, calculating the physic coordinate of the target object; and finally, calculating the behavior data of the target object according to the physic coordinate, corresponding frames and video frame rates. Compared with the prior art, the method is based on videos, and utilizes a target recognition algorithm, a target tracking algorithm and the corresponding relation between a video pixel coordinate and a physic coordinate, thereby obtaining the physic coordinate of a target object in a video; and then, according to the frame rate and frame number of the video, the method calculates target object behavior data, thereby providing real, effective, objective and vast data support for research of pedestrian microscopic behaviors.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a video-based acquisition method of target object behavior data and a video-based target object behavior data acquisition device. Background technique [0002] With the rapid development of the economy and the acceleration of urbanization, the rapid growth of travel demand has increasingly diversified and complicated the requirements of the passenger transport system. The advantages of frequency, high efficiency, and large capacity have gradually become one of the important components of the urban public transport system. As a node with a strong radiation effect in the urban rail transit network, the urban rail transit hub has always regarded passenger transport organization and service as the core task of station operation, and the issue of passenger flow line organization is also an important indicator to measure the passenger transport capacity of the hub and ...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the pedestrian behavior research at home and abroad is based on mathematical theory and computer means. Although some achievements have been achieved, because the pedestrian behavior data generally come from experiments or simulations, the amount of data is small, and it is difficult to be true, effective, and accurate. Objectively reflect the behavior of pedestrians

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