Pedestrian detection method based on machine vision and pedestrian anti-collision warning system based on machine vision

Abstract

The invention discloses a pedestrian detection method based on machine vision and a pedestrian anti-collision warning system based on machine vision. The method includes: acquiring an image of a place in front of an automobile, pre-positioning pedestrians in the processed image, judging a pre-positioned pedestrian area to position the pedestrian area accurately, measuring the distance between the pedestrians and the automobile and judging whether the pedestrians are in a dangerous area or not, and warning the pedestrians in the collision dangerous area. The anti-collision warning system comprises an image acquisition unit, a pedestrian positioning unit, a pedestrian distance measuring unit, and a collision possibility analyzing unit. By using a pedestrian classifier to detect the pedestrians on roads, individual characteristics of the pedestrians are blurred, influence of individual differences and illumination to detecting results is reduced, detection efficiency of the pedestrians is improved. The anti-collision warning system is further used to judge possibility of accidents so as to give warning signals to a driver, so that safety of automotive vehicle driving on the roads is improved.

Description

technical field [0001] The invention relates to a pedestrian detection method and a pedestrian anti-collision early warning system, in particular to a machine vision-based pedestrian detection method and a pedestrian anti-collision early warning system that can accurately determine the position of pedestrians and the possibility of dangerous accidents. Background technique [0002] Pedestrian detection and warning system means that through the detection function of certain sensors (such as radar and camera), the road traffic information in front of the driving car is obtained, including relatively moving and relatively stationary pedestrians or objects, and then through the background system, the sensor The acquired signals are processed and analyzed, and various physical parameter measurement and computer vision recognition technologies are used to realize the detection and tracking of pedestrians, and by calculating the relative displacement and distance, the possibility of...

AI Technical Summary

Problems solved by technology

[0004] The principle of the motion-based method is to identify pedestrians by analyzing the periodicity of pedestrian gait. Its advantage is that it is less affected by color and light and has good robustness. The disadvantage is that it can only identify moving pedestrians and requires multiple frames. Affect real-time performance;

[0005] Based on the method of clear human body model, the principle is to construct a clear human body parameter model to represent pedestrians. Its advantage is that it has a clear model, which is convenient for dealing with posture and occlusion problems. Its disadvantage is that the modeling and solution are more complicated;

[0006] The method based on template matching, the principle is to represent pedestrians through templates, the advantage is that the calculation method is simple, the system overhead is small, the disadvantage is that many templates are needed to deal with the pose problem, and the matching is time-consuming;

[0007] Based on the method of statistical classification, the principle is to identify pedestrians through classifiers. Its advantage is that it does not need to manually set a large number of parameters and has good robustness. Its disadvantage is that it requires a large amount of training data and the training period is long.

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