Monocular vision range finding method based on geometric relation

Abstract

The invention discloses a monocular vision range finding method based on geometric relation, and the method comprises the following steps: S1, calculating the distance between a section straight line of a target object and a camera lens in a horizontal plane; S2, calculating the distance between a target object and the optical axis of a monocular lens through the triangle similarity principle. According to the projection model of a camera, the method obtains the relation between a road surface coordinate system and an image coordinate system through geometric derivation, is simple in calculation process, is low in calculation complexity, and is lower in requirements for hardware. Meanwhile, the method can reach higher precision, and the error of the method is less than 0.5m. The method can effectively calculate the distance between the front vehicles or other obstacles under the conditions that the hardware configuration condition is very simple and almost no additional load and electric quantity is added, thereby achieving the effective avoidance. The method and device are good in application prospect, such as the technical field of automobile automatic driving or intelligent robot walking.

Description

technical field [0001] The invention belongs to the technical field of monocular data measurement, is mainly applied to the field of autonomous mobile robots and intelligent vehicle visual navigation assistance systems, and in particular relates to a monocular visual ranging method based on geometric relationships. Background technique [0002] Monocular measurement data, that is, use a single camera to shoot a single picture of the front object, and use the camera parameters, the object coordinate points in the picture, the relationship between the image distance and the image size to obtain the object distance. The imaging principle is as follows: figure 1 shown. [0003] In the existing non-contact ranging technology field, the most involved theories and methods are mainly multi-eye (usually binocular) ranging and laser ranging. Although binocular stereo vision has been studied for more than 20 years, its technology has been greatly developed. However, no matter from th...

AI Technical Summary

Problems solved by technology

Although the accuracy of laser ranging is high, its directivity is too strong, so the divergence is very low. If it is necessary to solve the problem of multi-target ranging, there are many problems such as excessive resource consumption, low accuracy, and relatively high cost.

[0004] Other ranging methods, such as infrared ranging, have problems such as low accuracy, short distance, and poor directionality. Ultrasonic ranging has strong anti-interference ability, but low accuracy and high cost.

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