Method and device for determining position of obstacle in image, equipment and medium

Abstract

The embodiment of the invention discloses a method and device for determining the position of an obstacle in an image, equipment and a medium, can be used for automatic driving, and relates to the technical field of image processing. The method comprises the following steps: obtaining a currently photographed driving environment image; determining a shielded part of a target obstacle in the driving environment image, and determining an initial coordinate of an unshielded part of the target obstacle; determining prediction coordinates of the shielded part by using a preset position prediction algorithm; and determining the current position of the target obstacle in the driving environment image based on the prediction coordinates and the initial coordinates. According to the embodiment of the invention, the accuracy of obstacle positioning in the driving environment image can be improved.

Description

technical field [0001] The embodiments of the present application relate to computer technology, specifically to the field of image processing technology, and in particular to a method, device, device and medium for determining the position of obstacles in an image, which can be used for automatic driving. Background technique [0002] In the application scenario of the Internet of Vehicles, accurate detection and positioning of obstacles in the driving environment can assist the vehicle system to obtain more environmental information. [0003] However, obstacles in the driving environment will inevitably be blocked. For example, using a camera deployed on the road to photograph a stationary obstacle in the driving environment, when the stationary obstacle is blocked by other objects, the accuracy of the position of the obstacle detected based on the photographed driving environment image will decrease, resulting in the stationary The detection position of the obstacle on t...

AI Technical Summary

Problems solved by technology

[0003] However, obstacles in the driving environment will inevitably be blocked

For example, using a camera deployed on the road to photograph a stationary obstacle in the driving environment, when the stationary obstacle is blocked by other objects, the accuracy of the position of the obstacle detected based on the photographed driving environment image will decrease, resulting in the stationary The detection position of the obstacle on the multi-frame driving environment image jumps

Furthermore, on the visual detection result display interface, the detection frame used to represent the position of the obstacle appears to shake continuously, which affects the effect of obstacle tracking based on the obstacle detection position, or affects the effect of multi-camera obstacle fusion

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