Vehicle target joint cognition method and system based on point cloud and image data

A technology of image data and point cloud data, applied in the field of vehicle target joint cognition method and system, can solve the problems of unmanned driving and low precision, and achieve high flexibility, generalization ability and strong generalization ability Effect

Active Publication Date: 2019-07-12
武汉环宇智行科技有限公司
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Problems solved by technology

[0004] The existing technology can combine the detection of optical images and three-dimensional point cloud data, and match the image features and three-dimensional point cloud features through the convolutional neural network, so as to obtain the outer rectangular frame of the target, which is used

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  • Vehicle target joint cognition method and system based on point cloud and image data
  • Vehicle target joint cognition method and system based on point cloud and image data
  • Vehicle target joint cognition method and system based on point cloud and image data

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[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0029] like figure 1 As shown, the vehicle target joint recognition method based on point cloud and influence data of the present invention includes the following steps:

[0030] Step 1: Acquire the three-dimensional point cloud data of the lidar and the plane image of the image sensor, divide the three-dimensional point cloud data into a grid, obtain a plurality of voxels of the same size, and calculate the mass points of the three-dimensional point cloud in e...

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Abstract

The invention provides a vehicle target joint cognition method and system based on point cloud and image data. The system comprises a data level combination module, a deep learning target detection wood block and a combination cognition module. The data level combination module obtains three-dimensional point cloud data and image data, and fuses the point cloud data and the image data. Fusion datais collected by the deep learning target detection module to be subjected to feature level detection and recognition, a detection result is output. The joint cognition module judges the feature levelfusion detection result and the data level fusion detection result by adopting an evidence theory method, reliability distribution is obtained to serve as output, and detection stability and robustness are improved.

Description

technical field [0001] The invention relates to the field of unmanned driving technology, in particular to a method and system for joint recognition of vehicle targets based on point cloud and image data. Background technique [0002] An unmanned vehicle is a vehicle with autonomous driving behavior. On the basis of traditional vehicles, artificial intelligence modules such as environmental perception, intelligent decision-making, path planning, and behavior control are added, and then it can interact with the surrounding environment and rent out corresponding functions. Decision-making and action of mobile wheeled robots. [0003] Thanks to the rapid development of new sensor technology and its learning technology, a variety of sensors are used in unmanned driving to perform complete, accurate, robust and real-time perception of the surrounding environment. The process of environment perception mainly includes sensor calibration, structured road detection, unstructured roa...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/56G06N3/045G06F18/24G06F18/253
Inventor 李明曹晶石强谢兴
Owner 武汉环宇智行科技有限公司
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