3D object detection method based on monocular camera

A monocular camera and object detection technology, applied in the field of 3D object detection, can solve problems such as endangering the safety and reliability of horizontal and vertical control driving, passenger discomfort or injury, and inaccurate predictions

Pending Publication Date: 2021-06-01
HUIZHOU DESAY SV AUTOMOTIVE
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Problems solved by technology

[0004] However, the actual road surface cannot be completely flat. When the road surface is curved or uneven, these traditional methods will be affected.
For example, when the ground plane is assumed to be flat, it is actually uneven, curves on the driving surface can lead to inaccurate predictions, and distance estimates to obstacles in the environment can be over- or under-judged
In both cases, inaccurate distance estimation can have a direct negative impact on various maneuvers of the vehicle, potentially compromising lateral and longitudinal control or drivin

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Embodiment 1

[0058] This embodiment provides a 3D object detection method based on a monocular camera, and the implementation of the method is mainly based on a vehicle-mounted camera and a vehicle-mounted laser radar. There can be one or more car cameras and car lidars, and the number is not limited. The on-board camera and on-board lidar should be installed on the same side of the test vehicle as possible, or in a similar position, so as to obtain the original image data and lidar data from the same angle.

[0059] Such as Figure 1-Figure 6 As shown, a 3D object detection method based on a monocular camera includes the following steps:

[0060] 101. Establish a depth estimation model, where the depth estimation model is used to obtain a predicted depth map matched with original image data.

[0061] The main purpose of establishing a depth estimation model is to quickly obtain a predicted depth map that matches the original image data. In the specific process of establishing the depth...

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Abstract

The invention relates to a 3D object detection method based on a monocular camera, and the method comprises the steps: building a depth estimation model which is used for obtaining a prediction depth map matched with original image data; obtaining original image data through a vehicle-mounted camera; acquiring a predicted depth map matching the original image data by using the depth estimation model; detecting a target object in the original image data; and projecting the target object to the corresponding predicted depth map to generate an anchoring area, and performing 3D reconstruction on the anchoring area to obtain a three-dimensional coordinate value of the target object in the world coordinate system. According to the 3D object detection method, the three-dimensional coordinate information of the object can be obtained only by means of the monocular camera, the invention does not depend on the assumed basis that the road surface is completely flat, the cost is low, the detection precision is high, accurate reference data can be provided for a driver, the driving safety can be improved, and the invention has important use value.

Description

technical field [0001] The invention relates to the technical field of 3D object detection, in particular to a 3D object detection method based on a monocular camera. Background technique [0002] Detecting objects of interest and inferring their 3D properties is a central problem in computer vision and has achieved widespread applications. Especially in the past ten years, with the rapid development of unmanned driving technology and mobile robots, object detection has played an extremely important role in the perception system. Accurate and efficient perception systems can effectively ensure that the robot and other surrounding moving objects safety. In recent years, although 2D object detection has also been rapidly developed in unmanned driving systems, more improvements are still needed to convert detected objects from the image plane to real-world poses. The task of conventional 3D object detection usually relies heavily on depth sensors such as lidar or millimeter-w...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06T5/00G06T7/50
CPCG06T5/002G06T7/50G06T2207/20032G06V20/64G06V20/56G06F18/22G06F18/214
Inventor 黄梓航伍小军周航刘妮妮董萌陈炫翰
Owner HUIZHOU DESAY SV AUTOMOTIVE
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