Electric vehicle automatic detection method based on vehicle-mounted vision within blind zone

Abstract

The invention discloses an electric vehicle automatic detection method based on vehicle-mounted vision within a blind zone. The method includes the steps that sampled data are obtained and sample characteristic data are extracted firstly, and the characteristic data are trained through a training module to generate an Adaboost cascade classifier; online detection is carried out on input image data through a mode based on hypothesis generation and hypothesis verification, the input image data are input to the trained classifier, and positioning for an electric vehicle is completed. The method aims to improve road traffic security and reduce occurrence of accidents in the blind zone. The method improves detection efficiency on the premise of guaranteeing detection accuracy.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to an automatic detection method for electric vehicles in blind spots based on vehicle vision. Background technique [0002] With the continuous increase of car ownership, road traffic accidents and the number of casualties due to traffic accidents remain high, causing huge economic losses and casualties. Due to the lack of special protective equipment and other reasons, pedestrians and cyclists are the most vulnerable traffic participants and the main victims of traffic accidents. The occurrence of road traffic accidents is generally due to the driver's negligence, inexperience or the visual blind spot of the vehicle, especially the blind spot on the right side of the vehicle. When many drivers are asked why after a traffic accident, the answers they get are often "I didn't see it beforehand", "It was too sudden" or "I didn't stop in time after I found it", etc. These all show the ch...

AI Technical Summary

Problems solved by technology

[0004] From the perspective of computer vision, the detection of electric vehicles is extremely challenging: first, it has a relatively fast speed, which requires that the algorithm must be able to process visual data faster and realize recognition and judgment faster; second, The detection of electric vehicles includes both "people" and "objects", which are non-rigid to a certain extent. Different viewing angles will lead to changes in appearance, shape and other characteristics; moreover, changes in road conditions and pedestrian interference will be detected cause difficulty

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