Vehicle mileage calculation method based on double-eye vision

Abstract

The invention belongs to the technical field of autonomous navigation of intelligent traffic vehicles, and particularly relates to a vehicle mileage calculation method based on double-eye vision. The vehicle mileage calculation method comprises the following steps of obtaining a video stream of a double-eye camera which is fixedly arranged at the top part of a vehicle, and transmitting to a vehicular processor; respectively extracting the features of a left image and a right image from the image of each frame of video stream of the double-eye camera, combining with the features of a left image and a right image of the previous frame, and searching a matched feature point set by a feature matching method; according to the matched feature points of the previous frame, using a three-dimensional vision method to calculate the space coordinates of a corresponding three-dimensional point; re-projecting the space coordinates of the three-dimensional point in the previous step to the coordinates of a two-dimensional image of the existing frame, and using a GN iteration algorithm to solve the minimum error of re-projection, so as to solve the motion transformation value of the vehicle of the adjacent frame; according to the motion transformation value of the vehicle, accumulating and updating the mileage information of the vehicle motion. The vehicle mileage calculation method has the advantages that by matching and combining the quick features and the high-precision features, the precision is improved, and the calculating speed is guaranteed.

Description

technical field [0001] The invention belongs to the technical field of autonomous navigation of intelligent transportation vehicles, and in particular relates to a vehicle mileage calculation method based on binocular vision. Background technique [0002] In the urban road intelligent transportation system, vehicle positioning and navigation are very basic technical requirements, and are also the prerequisites for driverless driving and vehicle-vehicle communication. Existing positioning and navigation technologies mainly rely on GPS or wheel odometers. Although the accuracy can meet the general needs, in complex urban traffic, often due to the occlusion of buildings or environments such as tunnels, it is impossible to receive sufficient odometers. GPS signals, or due to vehicle slippage, wheel odometers are not accurate enough, causing navigation and positioning errors. The invention uses a binocular camera fixed on the top of the vehicle to collect the left and right imag...

AI Technical Summary

Problems solved by technology

The general framework of the vehicle-mounted binocular vision mileage calculation method can be summarized as feature extraction, feature matching, calculation transformation, etc. Existing methods often use a single feature, such as the Harris equicorner feature, although the calculation speed is fast, it is not robust enough. Complex and variable lighting environments tend to cause large errors, and if all high-precision features are used, such as SIFT or SURF, it is difficult to meet the real-time requirements. Therefore, it is necessary to combine the advantages and disadvantages of the two to quickly Feature detection is the main method. When the error is large, replace it with a feature with higher accuracy, so as to meet the real-time requirements while achieving accuracy.

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